Current Problems in Diagnostic Radiology最新文献

{"title":"Improving communication of unexpected findings: The radiology actional findings tracking (RAFT) program","authors":"Sydney Whalen ,&nbsp;Surbhi Trivedi ,&nbsp;Josi Herren ,&nbsp;Katherine Fuguitt ,&nbsp;James T. Bui","doi":"10.1067/j.cpradiol.2025.01.006","DOIUrl":"10.1067/j.cpradiol.2025.01.006","url":null,"abstract":"<div><div>Incidental findings are unexpected, actionable discoveries made on diagnostic imaging that have significant patient care and medicolegal implications if not well managed. Despite their importance, few systems exist to manage incidental findings. The Radiology Actionable Findings Tracking (RAFT) Program was developed to improve communication of incidental findings to radiologists, providers, and their patients. The RAFT template is incorporated into the electronic medical record and discloses important information such as: Finding, Acuity, Communication Status, and General Recommendation for follow-up. This data is automatically compiled into a spreadsheet monitored by a clinical coordinator who is responsible for notifying the primary care physician or referring provider. The alert is resolved once appropriate communication is made and the recommended follow-up measures are documented. Between January 2021 and June 2023, the program has tracked the communication of 2,243 incidental findings, for an average of 75 incidental findings each month. Of those total findings, 270 findings (12 %) triggered additional protocols for provider and patient notification with subsequent follow-up. The program is effective in improving communication of incidental findings and can serve as a valuable tool for radiologists, providers, and the patients they serve.</div></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"54 4","pages":"Pages 418-421"},"PeriodicalIF":1.5,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143506616","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":"Assessing asymmetric enhancement on breast MRI: Besting the diagnostic challenge with imaging and clinical clues","authors":"Stephane Chartier D.O. ,&nbsp;Jennifer Kramer M.D. ,&nbsp;Sheryl Jordan M.D. ,&nbsp;Alan Chiang M.D., Ph.D.","doi":"10.1067/j.cpradiol.2024.12.011","DOIUrl":"10.1067/j.cpradiol.2024.12.011","url":null,"abstract":"<div><div>Breast magnetic resonance imaging (MRI) has the highest sensitivity for breast cancer detection compared to other breast imaging modalities such as mammography and ultrasound. As a functional modality, it captures the increased angiogenic activity of breast cancer through gadolinium-based contrast enhancement. Normal breast tissue also enhances, albeit in distinct patterns termed background parenchymal enhancement (BPE). Asymmetric enhancement, i.e., when one breast enhances more prominently than the other, can pose a diagnostic challenge for interpreting radiologists as distinguishing suspicious nonmass enhancement (NME) versus benign asymmetric BPE can be difficult. Correlating with patient history and imaging findings can help differentiate benign versus suspicious patterns of asymmetric enhancement. We present a collection of cases illustrating clues helpful for assessing asymmetric enhancement encountered on breast MRI.</div></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"54 4","pages":"Pages 481-489"},"PeriodicalIF":1.5,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142928867","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":"Creation of nomograms that combine clinical, CT, and radiographic features to separate benign from malignant diseases using spiculation or (and) lobulation signs","authors":"Ruoxuan Wang ,&nbsp;Tianjie Qi","doi":"10.1067/j.cpradiol.2024.12.014","DOIUrl":"10.1067/j.cpradiol.2024.12.014","url":null,"abstract":"<div><h3>Background</h3><div>Distinguishing between benign and malignant pulmonary nodules based on CT imaging features such as the spiculation sign and/or lobulation sign remains challenging and these nodules are often misinterpreted as malignant tumors. this retrospective study aimed to develop a prediction model to estimate the likelihood of benign and malignant lung nodules exhibiting spiculation and/or lobulation signs.</div></div><div><h3>Methods</h3><div>A total of 500 patients with pulmonary nodules from June 2022 to August 2024 were retrospectively analyzed. Among them, 190 patients with spiculation sign and lobar sign or both on CT scan were included in this study. This investigation collected the clinical information, preoperative chest CT imaging characteristics, and postoperative histopathologic results from patients.Univariate and multivariate logistic regression analyses were employed to identify independent risk factors, from which a prediction model and nomogram were developed. In addition, The model performance was assessed through receiver operating characteristic(ROC) curve analysis, calibration curve analysis, and decision curve analysis (DCA).</div></div><div><h3>Results</h3><div>In our study, 190 patients with pulmonary nodules underwent lung biopsy in 10 patients and surgical resection in 180 patients, of whom 53 were benign nodules and 137 were malignant nodules. When combined with the spiculation sign or (and) the lobulation sign, the vascular cluster sign, bronchial architectural distortion, bubble-like translucent area, nodule density, and CEA were found to be significant independent predictors for determining the benignity and malignancy of pulmonary nodules. The nomogram prediction model demonstrated high predictive accuracy with an area under the ROC curve (AUC) of 0.904. Furthermore, the model's calibration curve demonstrated adequate calibration. DCA confirmed the prediction model's validity.</div></div><div><h3>Conclusion</h3><div>The model can assist clinicians in making more accurate preoperative diagnoses and in guiding clinical decision-making regarding treatment, potentially reducing unnecessary surgical interventions.</div></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"54 4","pages":"Pages 443-448"},"PeriodicalIF":1.5,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143026223","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":"Corrigendum to “Original Article: The history of Women in Radiology (WIR) programs at two academic institutions: How we did it and how we merged best practices” [Current Problems in Diagnostic Radiology 54 (2025) 35-39]","authors":"Stacy E. Smith ,&nbsp;Dania Daye ,&nbsp;Carmen Alvarez ,&nbsp;Kirti A. Magudia ,&nbsp;Catherine H. Phillips ,&nbsp;Sandra Rincon ,&nbsp;Miriam A. Bredella ,&nbsp;Teresa Victoria","doi":"10.1067/j.cpradiol.2024.12.013","DOIUrl":"10.1067/j.cpradiol.2024.12.013","url":null,"abstract":"","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"54 2","pages":"Page 286"},"PeriodicalIF":1.5,"publicationDate":"2024-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142901134","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":"The “pseudo-pulmonary AVM sign”: an aid to the diagnosis of histoplasmosis and differentiation from pulmonary arteriovenous malformations","authors":"Marlee Mason-Maready MD ,&nbsp;Kiran Nandalur MD ,&nbsp;Said Khayyata MD ,&nbsp;Sayf Al-Katib MD","doi":"10.1067/j.cpradiol.2024.12.003","DOIUrl":"10.1067/j.cpradiol.2024.12.003","url":null,"abstract":"<div><div>The diagnostic algorithm for histoplasmosis highlights the importance of imaging and emphasizes the role of the radiologist in the diagnostic workup. Here we describe a case series of patients with a novel sign of lung involvement in histoplasmosis which we have coined the Pseudo-Pulmonary Arteriovenous Malformation (PAVM) sign, the usage of which would help in the imaging diagnosis of histoplasmosis aid by distinguishing it from PAVMs. PAVMs carry risk for serious complications such as systemic emboli and may require treatment; whereas, histoplasmomas do not. Differentiation of histoplasmosis from other diagnoses can be made with laboratory studies, but may require bronchoscopy, biopsy, or both. Meanwhile, PAVMs should not be biopsied due to risk of bleeding. For these reasons, distinguishing PAVMs and histoplasmosis radiologically therefore greatly impacts clinical management, and it is important for radiologists to be aware of this appearance of histoplasmosis to avoid misinterpretation as PAVM and effectively inform clinical care.</div></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"54 4","pages":"Pages 455-459"},"PeriodicalIF":1.5,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142831498","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":"How I Do It: Leveraging AutoHotkey and programmable peripheral devices for high efficiency diagnostic radiology","authors":"Ryan P. Joyce MD","doi":"10.1067/j.cpradiol.2024.12.012","DOIUrl":"10.1067/j.cpradiol.2024.12.012","url":null,"abstract":"<div><div>This paper discusses the use of AutoHotkey (AHK) and programmable peripheral computing devices to enhance the workflow of diagnostic radiologists. Multiple features designed and coded by an emergency teleradiologist to optimize efficiency and complete redundant tasks with ease are presented. The full AutoHotkey script, which currently supports Visage PACS, PowerScribe 360, and Epic EHR, is available in the article appendix. Recommended peripheral devices and schematics for easy integration with the AutoHotkey script are provided. Downloadable peripheral device profiles for the recommended devices are available in the appendix. The combination of task automation, achieved with AutoHotkey, and the thoughtful configuration of programmable peripheral devices, providing easy access to task automations, can lead to improved ergonomics, increased efficiency, productivity, and job satisfaction.</div></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"54 3","pages":"Pages 318-331"},"PeriodicalIF":1.5,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142873662","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":"Spectrum of errors in nodule detection and characterization using machine learning: A pictorial essay","authors":"Jabi E. Shriki MD (Associate Professor Staff Physician) ,&nbsp;Ted Selker PhD (Research Professor) ,&nbsp;Kristina Crothers MD (Professor Chief) ,&nbsp;Mark Deffebach MD (Professor Chief) ,&nbsp;Safia Cheeney MD (Assistant Professor Chief) ,&nbsp;Jeffrey Edelman MD (Associate Professor Staff Physician) ,&nbsp;Anupama Brixey MD (Assistant Professor Staff Physician) ,&nbsp;Mark Tubay MD (Assistant Professor Staff Physician) ,&nbsp;Laura Spece MD ,&nbsp;Sirish Kishore MD (Associate Professor Staff Physician)","doi":"10.1067/j.cpradiol.2024.10.039","DOIUrl":"10.1067/j.cpradiol.2024.10.039","url":null,"abstract":"<div><div>In academic and research settings, computer-aided nodule detection software has been shown to increase accuracy, efficiency, and throughput. However, radiologists need to be familiar with the spectrum of errors that can occur when these algorithms are employed in routine clinical settings. We review the spectrum of errors that may result from computer-aided nodule detection. In our clinical practice, we have seen errors in nodule detection, nodule localization, and nodule characterization. Each of these categories are demonstrated with illustrative cases. Through these illustrative cases, readers can be more familiar with nuances and pitfalls generated by computer-aided detection software. Although computer-aided nodule detection software is rapidly advancing, radiologists still need to thoroughly review images with mindfulness of some of the errors that can be generated by AI platforms for nodule detection.</div></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"54 2","pages":"Pages 273-280"},"PeriodicalIF":1.5,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142866844","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 gallstones and complications","authors":"Davin J. Evanson ,&nbsp;Lana Elcic ,&nbsp;Jennifer W. Uyeda ,&nbsp;Maria Zulfiqar","doi":"10.1067/j.cpradiol.2024.12.007","DOIUrl":"10.1067/j.cpradiol.2024.12.007","url":null,"abstract":"<div><div>Gallbladder pathologies caused by gallstones are commonly encountered in clinical practice, making accurate diagnosis critical for effective patient management. Radiologists play a key role in differentiating these conditions through imaging interpretation, ensuring that appropriate treatment is initiated. The imaging features of gallstone associated diseases are classified into various categories, such as inflammatory conditions, benign lesions, malignant tumors, and associated complications. A comprehensive understanding of these categories and their radiologic manifestations is essential for accurate diagnosis and management of gallbladder pathology. By integrating clinical knowledge with radiologic findings, clinicians and radiologists will be equipped with practical tools to identify and distinguish between different gallstone causing conditions.</div></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"54 3","pages":"Pages 392-403"},"PeriodicalIF":1.5,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142831495","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":"A stroke imaging protocol in patients with a history of contrast-induced anaphylaxis","authors":"Gabriel M Virador MD ,&nbsp;Rahul B Singh MBBS ,&nbsp;Vivek Gupta MD ,&nbsp;Dinesh Rao MD ,&nbsp;Josephine F Huang MD ,&nbsp;Leslie V Simon DO ,&nbsp;Sukhwinder J S Sandhu MD","doi":"10.1067/j.cpradiol.2024.12.001","DOIUrl":"10.1067/j.cpradiol.2024.12.001","url":null,"abstract":"<div><div>The need for emergent, contrast-enhanced neuroimaging in stroke patients with a history of severe reaction to iodinated contrast represents a unique dilemma in emergency departments. There is currently a lack of evidence-based management protocols for these cases. We describe a protocol established at our institution, based off American College of Radiology (ACR) guidelines and institutional experience, to guide decision-making in these scenarios.</div></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"54 2","pages":"Pages 143-146"},"PeriodicalIF":1.5,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142822866","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":"Arachnoid granulations: Dynamic nature and review","authors":"Andrew Wai Kei Ko,&nbsp;Ahmed Abdelmonem,&nbsp;M. Reza Taheri","doi":"10.1067/j.cpradiol.2024.12.006","DOIUrl":"10.1067/j.cpradiol.2024.12.006","url":null,"abstract":"<div><div>Arachnoid granulations have been known for centuries yet remain incompletely understood. While traditionally associated with cerebrospinal fluid transport, the precise mechanism remains uncertain. This manuscript reviews the literature on the anatomy, histology, and imaging findings of arachnoid granulations and their mimickers and anomalous variations. We highlight variations in incidence, size, and characteristics of arachnoid granulations on imaging, and hypothesize that these variations may be explained by arachnoid granulations being dynamic secondary to varying functionality. We review the pathophysiologic role of arachnoid granulations in pathologies related to hydrocephalus, neurodegenerative disorders, and intracranial hypertension and hypotension. A further understanding of arachnoid granulations, their mechanism in cerebrospinal fluid transport, and change over time may provide a basis for future imaging markers and therapies.</div></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"54 2","pages":"Pages 265-272"},"PeriodicalIF":1.5,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142831494","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}