Current Problems in Diagnostic Radiology最新文献

{"title":"Evaluation of Hepatocellular Carcinoma Surveillance with Contrast-enhanced MRI in a High-Risk Western European Cohort","authors":"Federico I.F. Fiduzi MD ,&nbsp;François E.J.A. Willemssen MD ,&nbsp;Céline van de Braak MSc ,&nbsp;Quido G. de Lussanet de la Sablonière MD, PhD ,&nbsp;Jan N.M. IJzermans MD, PhD ,&nbsp;Daniel Bos MD, PhD ,&nbsp;Robert A. de Man MD, PhD ,&nbsp;Roy S. Dwarkasing MD, PhD","doi":"10.1067/j.cpradiol.2024.07.001","DOIUrl":"10.1067/j.cpradiol.2024.07.001","url":null,"abstract":"<div><h3>Aim</h3><p>To investigate the utilization of MRI using a MRI liver protocol with extracellular contrast-enhanced series for hepatocellular carcinoma (HCC) surveillance in high-risk patients.</p></div><div><h3>Methods</h3><p>Consecutive high-risk patients of a western European cohort who underwent repeated liver MRI for HCC screening were included. Lesions were registered according to the Liver Reporting &amp; Data System (LIRADS) 2018. HCC was staged as very early stage HCC (BCLC stage 0) and more advanced stages of HCC (BCLC stage A-D). Differences in time interval between MRI's for BCLC stage 0 and stage A-D were calculated with the Mann-Whitney U test. The HCC cumulative incidence at one-, three- and five years was calculated with the Kaplan Meier estimator.</p></div><div><h3>Results</h3><p>From 2010 to 2019 a total of 240 patients were included (71% male; median age: 57 years; IQR: 50-64 years) with 1350 MRI's. Most patients (83 %) had cirrhosis with hepatitis C as the most common underlying cause. Patients underwent on average four MRI's (IQR: 3-7). Forty-two patients (17.5%) developed HCC (52 HCC lesions: 43 LIRADS-5, eight LIRADS-4, and one LIRADS-TIV). Eighteen patients (43%) had BCLC stage 0 HCC with a significant shorter screening time interval (10 months; IQR: 6-21) compared to patients with BCLC stage A-D (21 months; IQR: 10-32) (p = 0.03). Thirty seven percent of patients with a LIRADS-3 lesion (n=43) showed HCC development within twelve months (median: 7.4 months). One, three- and five-year HCC cumulative incidence in cirrhotic patients was 1%, 10% and 17%, respectively.</p></div><div><h3>Conclusion</h3><p>High-risk patients who underwent surveillance with contrast-enhanced MRI developed HCC in 17.5 % during a follow up period of over 4 years median. Very early stage HCC was seen in compensated cirrhosis after a median time interval of 10 months. Later stages of HCC were related to prolonged screening time interval (median 21 months).</p></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"53 6","pages":"Pages 709-716"},"PeriodicalIF":1.5,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0363018824001129/pdfft?md5=6a0b5700244a00089ae25b4abfad353a&pid=1-s2.0-S0363018824001129-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141604646","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":"Computed tomography (CT) derived radiomics to predict post-operative disease recurrence in gastric cancer; a systematic review and meta-analysis","authors":"Niall J. O'Sullivan ,&nbsp;Hugo C. Temperley ,&nbsp;Michelle T. Horan ,&nbsp;Benjamin M. Mac Curtain ,&nbsp;Maeve O'Neill ,&nbsp;Claire Donohoe ,&nbsp;Narayanasamy Ravi ,&nbsp;Alison Corr ,&nbsp;James F.M. Meaney ,&nbsp;John V. Reynolds ,&nbsp;Michael E. Kelly","doi":"10.1067/j.cpradiol.2024.07.011","DOIUrl":"10.1067/j.cpradiol.2024.07.011","url":null,"abstract":"<div><h3>Introduction</h3><p>Radiomics offers the potential to predict oncological outcomes from pre-operative imaging in order to identify ‘high risk’ patients at increased risk of recurrence. The application of radiomics in predicting disease recurrence provides tailoring of therapeutic strategies. We aim to comprehensively assess the existing literature regarding the current role of radiomics as a predictor of disease recurrence in gastric cancer.</p></div><div><h3>Methods</h3><p>A systematic search was conducted in Medline, EMBASE, and Web of Science databases. Inclusion criteria encompassed retrospective and prospective studies investigating the use of radiomics to predict post-operative recurrence in ovarian cancer. Study quality was assessed using the QUADAS-2 and Radiomics Quality Score tools.</p></div><div><h3>Results</h3><p>Nine studies met the inclusion criteria, involving a total of 6,662 participants. Radiomic-based nomograms demonstrated consistent performance in predicting disease recurrence, as evidenced by satisfactory area under the receiver operating characteristic curve values (AUC range 0.72 - 1). The pooled AUCs calculated using the inverse-variance method for both the training and validation datasets were 0.819 and 0.789 respectively</p></div><div><h3>Conclusion</h3><p>Our review provides good evidence supporting the role of radiomics as a predictor of post-operative disease recurrence in gastric cancer. Included studies noted good performance in predicting their primary outcome. Radiomics may enhance personalised medicine by tailoring treatment decision based on predicted prognosis.</p></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"53 6","pages":"Pages 717-722"},"PeriodicalIF":1.5,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141713994","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":"Cybersecurity in radiology: Cautionary Tales, Proactive Prevention, and What to do When You Get Hacked","authors":"Xuan V. Nguyen MD, PhD ,&nbsp;Jonelle M. Petscavage-Thomas MD, MPH ,&nbsp;Christopher M. Straus MD ,&nbsp;Ichiro Ikuta MD, MMSc","doi":"10.1067/j.cpradiol.2024.07.010","DOIUrl":"10.1067/j.cpradiol.2024.07.010","url":null,"abstract":"<div><div>To improve awareness and understanding of cybersecurity threats to radiology practice and better equip healthcare practices to manage cybersecurity risks associated with medical imaging, this article reviews topics related to cybersecurity in healthcare, with emphasis on common vulnerabilities in radiology operations. This review is intended to assist radiologists and radiology administrators who are not information technology specialists to attain an updated overview of relevant cybersecurity concepts and concerns relevant to safe and effective practice of radiology and provides a succinct reference for individuals interested in learning about imaging-related vulnerabilities in healthcare settings. As cybersecurity incidents have become increasingly common in healthcare, we first review common cybersecurity threats in healthcare and provide updates on incidence of healthcare data breaches, with emphasis on the impact to radiology. Next, we discuss practical considerations on how to respond to a healthcare data breach, including notification and disclosure requirements, and elaborate on a variety of technical, organizational, and individual actions that can be adopted to minimize cybersecurity risks applicable to radiology professionals and administrators. While emphasis is placed on specific vulnerabilities within radiology workflow, many of the preventive or mitigating strategies are also relevant to cybersecurity within the larger digital healthcare arena. We anticipate that readers, upon completing this review article, will gain a better appreciation of cybersecurity issues relevant to radiology practice and be better equipped to mitigate cybersecurity risks associated with medical imaging.</div></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"54 2","pages":"Pages 245-250"},"PeriodicalIF":1.5,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141604644","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":"Simplifying risk stratification for thyroid nodules on ultrasound: validation and performance of an artificial intelligence thyroid imaging reporting and data system","authors":"Benjamin Wildman-Tobriner ,&nbsp;Jichen Yang ,&nbsp;Brian C. Allen ,&nbsp;Lisa M. Ho ,&nbsp;Chad M. Miller ,&nbsp;Maciej A. Mazurowski","doi":"10.1067/j.cpradiol.2024.07.006","DOIUrl":"10.1067/j.cpradiol.2024.07.006","url":null,"abstract":"<div><h3>Purpose</h3><p>To validate the performance of a recently created risk stratification system (RSS) for thyroid nodules on ultrasound, the Artificial Intelligence Thyroid Imaging Reporting and Data System (AI TI-RADS).</p></div><div><h3>Materials and methods</h3><p>378 thyroid nodules from 320 patients were included in this retrospective evaluation. All nodules had ultrasound images and had undergone fine needle aspiration (FNA). 147 nodules were Bethesda V or VI (suspicious or diagnostic for malignancy), and 231 were Bethesda II (benign). Three radiologists assigned features according to the AI TI-RADS lexicon (same categories and features as the American College of Radiology TI-RADS) to each nodule based on ultrasound images. FNA recommendations using AI TI-RADS and ACR TI-RADS were then compared and sensitivity and specificity for each RSS were calculated.</p></div><div><h3>Results</h3><p>Across three readers, mean sensitivity of AI TI-RADS was lower than ACR TI-RADS (0.69 vs 0.72, p &lt; 0.02), while mean specificity was higher (0.40 vs 0.37, p &lt; 0.02). Overall total number of points assigned by all three readers decreased slightly when using AI TI-RADS (5,998 for AI TI-RADS vs 6,015 for ACR TI-RADS), including more values of 0 to several features.</p></div><div><h3>Conclusion</h3><p>AI TI-RADS performed similarly to ACR TI-RADS while eliminating point assignments for many features, allowing for simplification of future TI-RADS versions.</p></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"53 6","pages":"Pages 695-699"},"PeriodicalIF":1.5,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0363018824001105/pdfft?md5=fe14e9d3f34bb79cf92b3bf4aa953afd&pid=1-s2.0-S0363018824001105-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141712372","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":"Increasing magic number and other trends in diagnostic radiology NRMP match data","authors":"Trenton Taros MD,&nbsp;Christopher Thomas Zoppo MD,&nbsp;Anthony Michael Camargo BA,&nbsp;Carolynn Michelle DeBenedectis MD","doi":"10.1067/j.cpradiol.2024.07.014","DOIUrl":"10.1067/j.cpradiol.2024.07.014","url":null,"abstract":"<div><div>The magic number, or number of ranks needed to achieve a greater than 90 % chance of matching, has not been investigated for diagnostic radiology (DR). Somewhat reflective of a field's changing competitiveness, this individual metric can be useful for reassuring applicants or identifying a need to reach out to mentors. The NRMP's Charting Outcomes in the Match was accessed over the previous 10 cycles to assess changes to magic number and other match-related metrics. Over the last 10 cycles, there has been an increase in magic number for prospective radiologists. Based on the most 2022 recent report, the magic number was 14 compared to 5 and 2 in 2014 and 2016 respectively. Compared to the average US MD senior, those applying into DR were significantly more likely to match in 2014, 2016 and 2020 (p &lt; 0.01 for all), and significantly less likely to match in 2018 and 2022 (p = 0.03 and p &lt; 0.01, respectively). This trend has had important consequences for applicants and programs as the incentive to apply more widely grows. The increasing magic number demonstrates increasing competitiveness in the field, which might be due to a positive job market, changing medical student preferences, or increased access to radiology electives and mentors. The 2024 Charting Outcomes document will be the first to include data from a class almost entirely affected by the change to a pass/fail Step1 and the new preference signaling supplement. It is currently unclear how either change will affect the overall competitiveness of the field and the magic number.</div></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"54 2","pages":"Pages 242-244"},"PeriodicalIF":1.5,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141636229","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":"ChatGPT and assistive AI in structured radiology reporting: A systematic review","authors":"Ethan Sacoransky BSc ,&nbsp;Benjamin Y.M. Kwan MD ,&nbsp;Donald Soboleski MD","doi":"10.1067/j.cpradiol.2024.07.007","DOIUrl":"10.1067/j.cpradiol.2024.07.007","url":null,"abstract":"<div><h3>Introduction</h3><p>The rise of transformer-based large language models (LLMs), such as ChatGPT, has captured global attention with recent advancements in artificial intelligence (AI). ChatGPT demonstrates growing potential in structured radiology reporting—a field where AI has traditionally focused on image analysis.</p></div><div><h3>Methods</h3><p>A comprehensive search of MEDLINE and Embase was conducted from inception through May 2024, and primary studies discussing ChatGPT's role in structured radiology reporting were selected based on their content.</p></div><div><h3>Results</h3><p>Of the 268 articles screened, eight were ultimately included in this review. These articles explored various applications of ChatGPT, such as generating structured reports from unstructured reports, extracting data from free text, generating impressions from radiology findings and creating structured reports from imaging data. All studies demonstrated optimism regarding ChatGPT's potential to aid radiologists, though common critiques included data privacy concerns, reliability, medical errors, and lack of medical-specific training.</p></div><div><h3>Conclusion</h3><p>ChatGPT and assistive AI have significant potential to transform radiology reporting, enhancing accuracy and standardization while optimizing healthcare resources. Future developments may involve integrating dynamic few-shot prompting, ChatGPT, and Retrieval Augmented Generation (RAG) into diagnostic workflows. Continued research, development, and ethical oversight are crucial to fully realize AI's potential in radiology.</p></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"53 6","pages":"Pages 728-737"},"PeriodicalIF":1.5,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0363018824001130/pdfft?md5=e3006ef32f98fe95868a662fec5d5a58&pid=1-s2.0-S0363018824001130-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141617846","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":"Lessons learned from rebranding a radiology education facebook page","authors":"","doi":"10.1067/j.cpradiol.2024.07.012","DOIUrl":"10.1067/j.cpradiol.2024.07.012","url":null,"abstract":"<div><h3>Objective</h3><p>In May 2009, we created a Facebook page for radiology education. While we shared a host of learning materials such as case images, quiz questions, and medical illustrations, we also posted world news, music, and memes. In February 2023, we eliminated everything from the site not related to radiology education. Our aim was to determine how focusing on radiology education alone would affect audience growth for our Facebook page.</p></div><div><h3>Materials and methods</h3><p>We exported our Facebook post data for the dates March 1, 2023 through February 29, 2024, to represent the full calendar year after we revised our content presentation, which we compared to data from November 1, 2020 to October 31, 2021. The mean and standard deviation for each post type's reach for 2023/24 were analyzed and compared against the 2020/21 statistics, and Wilcoxon rank sum tests were used to obtain p-values. Linear regressions for each year were performed to understand the relationship between reach and engagement.</p></div><div><h3>Results</h3><p>A total of 4,270 posts were included in our new analysis. Our average number of posts per day decreased from 24.8 to 11.71, reducing by more than half the amount of content shared to our social media page. Our posts had a mean overall reach of 4,660—compared to 1,743 in 2021 (p=0.0000). There was a statistically significant increase in reach for posts on artificial intelligence, case images, medical illustrations, pearls, quiz images, quiz videos, slideshow images, and both types of instructional videos (p&lt;0.005). For both 2021 and 2024, the linear regression slopes were positive (y=0.0687x−65.0279 and y=0.006334x+21.3425, respectively).</p></div><div><h3>Conclusions</h3><p>Facebook and other social media have been found to be helpful sources for radiology education. Our experience and statistics with radiology education via social media may help other radiology educators better curate their own pages. To optimize experiences for students, professionals, and other users, and to reach more people, we found that providing readily accessible radiology education is preferred to the social aspects of social media.</p></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"53 6","pages":"Pages 685-688"},"PeriodicalIF":1.5,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141602316","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":"“My attending really wants it!” Manual clinical decision support adjudicating the “better look” inpatient MRI at an academic medical center","authors":"","doi":"10.1067/j.cpradiol.2024.05.016","DOIUrl":"10.1067/j.cpradiol.2024.05.016","url":null,"abstract":"<div><h3>Objective</h3><p>MRI utilization in the United States is relatively higher than in other parts of the world and inpatient MRI utilization is particularly difficult to manage given the lack of direct reimbursement. Body MRI studies present an opportunity to reduce inpatient MRI utilization since they are generally the least emergent. Our objective was to use a targeted questionnaire to probe the necessity of inpatient body MRI orders and present an opportunity to either cancel them or transition them to the outpatient realm</p></div><div><h3>Methods</h3><p>A 9-item questionnaire was devised asking questions about the urgency of the inpatient MRI order including the urgent management question, an inpatient procedure or whether it was recommended by a consultant. Peer-to-peer discussion walking through each of the questions was conducted by radiology housestaff with the ordering clinicians and responses recorded.</p></div><div><h3>Results</h3><p>845 recorded responses reported a lack of specific clinical question in 23.9% of orders, 68.9% were recommended by a non-radiology consulting service and 16.1% were recommended by radiology studies. 17.0% orders were felt to be outpatient appropriate and 23.3% were considered possibly appropriate for the outpatient setting. 3.9% were canceled and 4.9% were transitioned to outpatient orders.</p></div><div><h3>Discussion</h3><p>Engaging in a focused discussion about the urgency and appropriateness of an inpatient MRI body order following a list of scripted questions has the potential to reduce utilization. This approach also highlights the relatively high rate of indication uncertainty among ordering clinicians and the central role of consultants in prompting orders.</p></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"53 5","pages":"Pages 583-587"},"PeriodicalIF":1.5,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141082979","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":"Complications of thoracic endovascular aneurysm repair (TEVAR): A pictorial review","authors":"","doi":"10.1067/j.cpradiol.2024.05.018","DOIUrl":"10.1067/j.cpradiol.2024.05.018","url":null,"abstract":"<div><p>Thoracic endovascular aneurysm repair (TEVAR) has replaced open surgical repair as the treatment of choice for several aortic conditions. Despite its lower morbidity and mortality, several TEVAR-related complications can occur and some of which may necessitate surgical or endovascular re-intervention. The current article reviews common and rare complications of TEVAR procedure with emphasis on complications identifiable on cross-sectional imaging and potential pitfalls of pre-procedural planning.</p></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"53 5","pages":"Pages 648-661"},"PeriodicalIF":1.5,"publicationDate":"2024-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141030706","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":"Same-day discharge after percutaneous renal cryoablation and its effect on 30 day hospital re-admission rates and post-procedural complications","authors":"","doi":"10.1067/j.cpradiol.2024.05.019","DOIUrl":"10.1067/j.cpradiol.2024.05.019","url":null,"abstract":"<div><h3>Purpose</h3><p>The purpose of this study is to identify if the local institutional shift from routine overnight observation to same-day discharge following percutaneous cryoablation (PCA) of renal tumors increases 30 day re-admission rates or serious adverse events (AEs).</p></div><div><h3>Materials and methods</h3><p>This retrospective study included 133 adult patients. PCA patients in calendar years 2018-2019 were routinely observed overnight in the hospital, comprising the control group (Group A). PCA patients in calendar years 2021-2022 were routinely discharged the same day, comprising the test group (Group B). Relevant demographic information, tumor characteristics, technical outcomes, and clinical outcomes were recorded.</p></div><div><h3>Results</h3><p>15 patients (11.3 %) from the total cohort were re-admitted to the hospital within 30 days of PCA for any reason. Seven patients (10.4 %) and eight patients (12.1 %) were re-admitted for any reason within 30 days in Group A and Group B, respectively, with no difference between the two groups (<em>p</em> = 0.76). Nine patients (6.8 %) from the total cohort were re-admitted to the hospital within 30 days for a diagnosis secondary to the procedure. Four patients (6 %) and five patients (7.6 %) were re-admitted within 30 days for reasons related to PCA in Group A and Group B, respectively, with no significant difference between the groups (<em>p =</em> 0.71). Eight patients (12 %) and four patients (6 %) had major AEs following PCA in Group A and Group B, respectively, with no difference between the two groups (<em>p =</em> 0.43).</p></div><div><h3>Conclusion</h3><p>Overall, the change in post-procedural care after PCA did not have a deleterious effect on 30 day re-admission rates or rates of major AEs.</p></div>","PeriodicalId":51617,"journal":{"name":"Current Problems in Diagnostic Radiology","volume":"53 6","pages":"Pages 689-694"},"PeriodicalIF":1.5,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0363018824000951/pdfft?md5=7d53198896cf3b28db66c3d7680d7327&pid=1-s2.0-S0363018824000951-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140913592","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}