Radiographics最新文献

{"title":"Invited Commentary: Important Features in MRI Reports of Soft-Tissue Tumors","authors":"Mark D. Murphey","doi":"10.1148/rg.240039","DOIUrl":"https://doi.org/10.1148/rg.240039","url":null,"abstract":"Abstract not available","PeriodicalId":54512,"journal":{"name":"Radiographics","volume":"40 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140842538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Acute Abdomen: A Case-based Survival Guide to What the Surgeon Wants to Know","authors":"John W. Kirby, Kelly K. Horst, James H. Boyum, Cornelius A. Thiels, Adam T. Froemming, Ashish Khandelwal","doi":"10.1148/rg.230161","DOIUrl":"https://doi.org/10.1148/rg.230161","url":null,"abstract":"Abstract not available","PeriodicalId":54512,"journal":{"name":"Radiographics","volume":"63 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140800393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Noncontrast MR Lymphography: A Noninvasive and Useful Imaging Modality","authors":"Lionel Arrivé, Hedi Chekir, Sanaâ El Mouhadi","doi":"10.1148/rg.240054","DOIUrl":"https://doi.org/10.1148/rg.240054","url":null,"abstract":"Abstract not available","PeriodicalId":54512,"journal":{"name":"Radiographics","volume":"17 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140800392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Response Evaluation Criteria in Gastrointestinal and Abdominal Cancers: Which to Use and How to Measure","authors":"Francesca Castagnoli, Justin Mencel, Derfel ap Dafydd, Jessica Gough, Brent Drake, Naami Charlotte Mcaddy, Samuel Joseph Withey, Angela Mary Riddell, Dow-Mu Koh, Joshua David Shur","doi":"10.1148/rg.230047","DOIUrl":"https://doi.org/10.1148/rg.230047","url":null,"abstract":"<p>As the management of gastrointestinal malignancy has evolved, tumor response assessment has expanded from size-based assessments to those that include tumor enhancement, in addition to functional data such as those derived from PET and diffusion-weighted imaging. Accurate interpretation of tumor response therefore requires knowledge of imaging modalities used in gastrointestinal malignancy, anticancer therapies, and tumor biology. Targeted therapies such as immunotherapy pose additional considerations due to unique imaging response patterns and drug toxicity; as a consequence, immunotherapy response criteria have been developed. Some gastrointestinal malignancies require assessment with tumor-specific criteria when assessing response, often to guide clinical management (such as watchful waiting in rectal cancer or suitability for surgery in pancreatic cancer). Moreover, anatomic measurements can underestimate therapeutic response when applied to molecular-targeted therapies or locoregional therapies in hypervascular malignancies such as hepatocellular carcinoma. In these cases, responding tumors may exhibit morphologic changes including cystic degeneration, necrosis, and hemorrhage, often without significant reduction in size. Awareness of pitfalls when interpreting gastrointestinal tumor response is required to correctly interpret response assessment imaging and guide appropriate oncologic management. Data-driven image analyses such as radiomics have been investigated in a variety of gastrointestinal tumors, such as identifying those more likely to respond to therapy or recur, with the aim of delivering precision medicine. Multimedia-enhanced radiology reports can facilitate communication of gastrointestinal tumor response by automatically embedding response categories, key data, and representative images.</p><p>^©RSNA, 2024</p><p>Test Your Knowledge questions for this article are available in the supplemental material.</p>","PeriodicalId":54512,"journal":{"name":"Radiographics","volume":"59 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140800473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation and Utilization of Flow Artifacts at CT","authors":"Caroline L. Robb, Kaitlin M. Marquis, Kacie L. Steinbrecher, Mark M. Hammer, Travis Henry, Sanjeev Bhalla, Constantine A. Raptis","doi":"10.1148/rg.230134","DOIUrl":"https://doi.org/10.1148/rg.230134","url":null,"abstract":"<p>Flow artifacts are commonly encountered at contrast-enhanced CT and can be difficult to discern from true pathologic conditions. Therefore, radiologists must be comfortable distinguishing flow artifacts from true pathologic conditions. This is of particular importance when evaluating the pulmonary arteries and aorta, as a flow artifact may be mistaken for a pulmonary embolism or dissection flap. Understanding the mechanics of flow artifacts and how these artifacts are created can help radiologists in several ways. First, this knowledge can help radiologists appreciate how the imaging characteristics of flow artifacts differ from true pathologic conditions. This information can also help radiologists better recognize the clinical conditions that predispose patients to flow artifacts, such as pneumonia, chronic lung damage, and altered cardiac output. By understanding when flow artifacts may be confounding the interpretation of an examination, radiologists can then know when to pursue other troubleshooting methods to assist with the diagnosis. In these circumstances, the radiologist can consider several troubleshooting methods, including adjusting the imaging protocols, recommending when additional imaging may be helpful, and suggesting which imaging study would be the most beneficial. Finally, flow artifacts can also be used as a diagnostic tool when evaluating the vascular anatomy, examples of which include the characterization of shunts, venous collaterals, intimomedial flaps, and alternative patterns of blood flow, as seen in extracorporeal membrane oxygenation circuits.</p><p>^©RSNA, 2024</p><p>Test Your Knowledge questions for this article are available in the supplemental material.</p>","PeriodicalId":54512,"journal":{"name":"Radiographics","volume":"23 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140800391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adrenal Vein Sampling: Tips and Tricks","authors":"Katsuhiro Kobayashi, Leen Alkukhun, Emily Rey, Abhijit Salaskar, Runa Acharya","doi":"10.1148/rg.230115","DOIUrl":"https://doi.org/10.1148/rg.230115","url":null,"abstract":"<p>Adrenal vein sampling (AVS) is the standard method for distinguishing unilateral from bilateral sources of autonomous aldosterone production in patients with primary aldosteronism. This procedure has been performed at limited specialized centers due to its technical complexity. With recent advances in imaging technology and knowledge of adrenal vein anatomy in parallel with the development of adjunctive techniques, AVS has become easier to perform, even at nonspecialized centers. Although rare, anatomic variants of the adrenal veins can cause sampling failure or misinterpretation of the sampling results. The inferior accessory hepatic vein and the inferior emissary vein are useful anatomic landmarks for right adrenal vein cannulation, which is the most difficult and crucial step in AVS. Meticulous assessment of adrenal vein anatomy on multidetector CT images and the use of a catheter suitable for the anatomy are crucial for adrenal vein cannulation. Adjunctive techniques such as intraprocedural cortisol assay, cone-beam CT, and coaxial guidewire-catheter techniques are useful tools to confirm right adrenal vein cannulation or to troubleshoot difficult blood sampling. Interventional radiologists should be involved in interpreting the sampling results because technical factors may affect the results. In rare instances, bilateral adrenal suppression, in which aldosterone-to-cortisol ratios of both adrenal glands are lower than that of the inferior vena cava, can be encountered. Repeat sampling may be necessary in this situation. Collaboration with endocrinology and laboratory medicine services is of great importance to optimize the quality of the samples and for smooth and successful operation.</p><p>^©RSNA, 2024</p><p>Test Your Knowledge questions for this article are available in the supplemental material.</p>","PeriodicalId":54512,"journal":{"name":"Radiographics","volume":"4 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140800404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Invited Commentary: The Double-edged Sword of Bias in Medical Imaging Artificial Intelligence","authors":"Pouria Rouzrokh, Bradley J. Erickson","doi":"10.1148/rg.230243","DOIUrl":"https://doi.org/10.1148/rg.230243","url":null,"abstract":"Abstract not available","PeriodicalId":54512,"journal":{"name":"Radiographics","volume":"50 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140623323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Encrusted Pyelitis","authors":"Augusto Goncalves Filho, Christian Gomez, Vaibhav Gulati, Tarek El-Diasty, Haytham Shebel","doi":"10.1148/rg.240002","DOIUrl":"https://doi.org/10.1148/rg.240002","url":null,"abstract":"Abstract not available","PeriodicalId":54512,"journal":{"name":"Radiographics","volume":"218 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140630009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding and Mitigating Bias in Imaging Artificial Intelligence","authors":"Ali S. Tejani, Yee Seng Ng, Yin Xi, Jesse C. Rayan","doi":"10.1148/rg.230067","DOIUrl":"https://doi.org/10.1148/rg.230067","url":null,"abstract":"<p>Artificial intelligence (AI) algorithms are prone to bias at multiple stages of model development, with potential for exacerbating health disparities. However, bias in imaging AI is a complex topic that encompasses multiple coexisting definitions. <i>Bias</i> may refer to unequal preference to a person or group owing to preexisting attitudes or beliefs, either intentional or unintentional. However, <i>cognitive bias</i> refers to systematic deviation from objective judgment due to reliance on heuristics, and <i>statistical bias</i> refers to differences between true and expected values, commonly manifesting as systematic error in model prediction (ie, a model with output unrepresentative of real-world conditions). Clinical decisions informed by biased models may lead to patient harm due to action on inaccurate AI results or exacerbate health inequities due to differing performance among patient populations. However, while inequitable bias can harm patients in this context, a mindful approach leveraging equitable bias can address underrepresentation of minority groups or rare diseases. Radiologists should also be aware of bias after AI deployment such as automation bias, or a tendency to agree with automated decisions despite contrary evidence. Understanding common sources of imaging AI bias and the consequences of using biased models can guide preventive measures to mitigate its impact. Accordingly, the authors focus on sources of bias at stages along the imaging machine learning life cycle, attempting to simplify potentially intimidating technical terminology for general radiologists using AI tools in practice or collaborating with data scientists and engineers for AI tool development. The authors review definitions of bias in AI, describe common sources of bias, and present recommendations to guide quality control measures to mitigate the impact of bias in imaging AI. Understanding the terms featured in this article will enable a proactive approach to identifying and mitigating bias in imaging AI.</p><p>Published under a CC BY 4.0 license.</p><p>Test Your Knowledge questions for this article are available in the supplemental material.</p><p>See the invited commentary by Rouzrokh and Erickson in this issue.</p>","PeriodicalId":54512,"journal":{"name":"Radiographics","volume":"50 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140623124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Imaging Assessment of Nontraumatic Pathologic Conditions at the Craniovertebral Junction: A Comprehensive Review","authors":"Letícia R. Morimoto, Daisy T. Kase, Paola G. Esmanhotto, Murilo A. Maciel, Ana C. L. Augusto, Patrick F. Catricala, Julia E. C. Anaya, Sugoto Mukherjee, Artur R. C. Fernandes, André Y. Aihara","doi":"10.1148/rg.230137","DOIUrl":"https://doi.org/10.1148/rg.230137","url":null,"abstract":"<p>Nontraumatic pathologic conditions of the craniovertebral junction encompass a range of conditions affecting the complex anatomy of this region without direct physical injury. These conditions include congenital syndromes that predispose individuals to ligamentous laxity, potentially leading to instability. Additionally, rare but noteworthy cases such as Grisel syndrome, a cause of pediatric torticollis, may arise without a traumatic trigger. Inflammatory diseases, including rheumatoid arthritis, ankylosing spondylitis, and crystal deposition, can lead to cervical instability and spinal cord compression. Infections at the upper cervical spine are dominated by tuberculosis, typically transmitted through hematologic or lymphatic routes with characteristic imaging findings. On the other hand, purulent bacterial infections in this area are rare. Furthermore, although tumors involving the structures of the craniovertebral junction are infrequent, they can lead to significant complications, albeit less frequently through cord compression and more commonly via pathologic fractures or subluxation. The craniocervical junction is a complex anatomic region comprising ligaments, bones, joints, and muscles that support the head's weight and enable its wide range of motion. Accurate recognition and understanding of the complex anatomy and the various nontraumatic pathologic conditions at the craniovertebral junction are pivotal for initiating timely and appropriate treatment strategies.</p><p>^©RSNA, 2024</p><p>Test Your Knowledge questions for this article are available in the supplemental material.</p>","PeriodicalId":54512,"journal":{"name":"Radiographics","volume":"57 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140623322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}