American Journal of Roentgenology最新文献

{"title":"Cost-Effectiveness of an Ultrasound-First Strategy in the Diagnostic Evaluation of Noncalcified Lesions Recalled From Screening Digital Breast Tomosynthesis.","authors":"B Bersu Ozcan, Yin Xi, Basak E Dogan, Jessica H Porembka","doi":"10.2214/AJR.24.31422","DOIUrl":"10.2214/AJR.24.31422","url":null,"abstract":"<p><p><b>BACKGROUND.</b> Ultrasound may be sufficient in the diagnostic evaluation of many noncalcified lesions recalled from screening digital breast tomosynthesis (DBT). In some scenarios, omission of diagnostic mammography can save health care costs. <b>OBJECTIVE.</b> The purpose of this study was to evaluate the cost-effectiveness of a strategy of performing ultrasound first versus diagnostic mammography first in the diagnostic evaluation of noncalcified lesions recalled from screening DBT. <b>METHODS.</b> Decision tree analysis was performed to compare ultrasound first versus diagnostic mammography first in the diagnostic evaluation of DBT-recalled noncalcified lesions from a U.S. health care system perspective with a 40-year horizon. The analysis used probabilities and prevalence information from published single-institution prospective data, additional literature-derived estimates of diagnostic test performance, and Medicare-allowable reimbursement rates. Health states were represented in a Markov chain model. For each strategy, the total cost and effectiveness (expressed in quality-adjusted life-years [QALYs]) were estimated. Cost-effectiveness was assessed through incremental cost-effectiveness ratios (ICERs) and incremental net monetary benefit, with use of a willingness-to-pay (WTP) threshold of US$100,000 per QALY gained. Deterministic sensitivity analyses were performed to estimate the impact of different input parameters, and probabilistic sensitivity analysis with Monte Carlo simulations was conducted to estimate the impact of combined uncertainty across parameters. <b>RESULTS.</b> In the base-case scenario, for diagnostic evaluation of DBT-recalled noncalcified lesions, a strategy of performing ultrasound first versus diagnostic mammography first resulted in more cost savings (total cost, US$17,672 vs US$18,323) and greater cost-effectiveness (QALYs, 23.1309 vs 23.1306) over the 40-year horizon. The ultrasound-first strategy resulted in an ICER of -2,170,000 (expressed as U.S. dollars per QALY) and an incremental net monetary benefit of US$681 versus the diagnostic mammography-first strategy. Therefore, performing ultrasound first was deemed the more cost-effective strategy at the WTP threshold. In deterministic sensitivity analyses, the most important driver of cost-effectiveness was lost utility from delayed diagnosis, followed by the relative sensitivities of ultrasound and diagnostic mammography. In probabilistic sensitivity analysis, ultrasound first was the better strategy in 93.0% of iterations. <b>CONCLUSION.</b> A strategy of performing ultrasound first, with or without diagnostic mammography, is more cost-effective than a traditional strategy of conducting diagnostic mammography first. <b>CLINICAL IMPACT.</b> This cost-effectiveness analysis supports the growing prioritization of ultrasound as the primary method for evaluating DBT-recalled noncalcified lesions.</p>","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141857199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Habitat Imaging With Tumoral and Peritumoral Radiomics for Prediction of Lung Adenocarcinoma Invasiveness on Preoperative Chest CT: A Multicenter Study.","authors":"Youlan Shang, Ying Zeng, Shiwei Luo, Yisong Wang, Jiaqi Yao, Ming Li, Xiaoying Li, Xiaoyan Kui, Hao Wu, Kangxu Fan, Zhi-Cheng Li, Hairong Zheng, Ge Li, Jun Liu, Wei Zhao","doi":"10.2214/AJR.24.31675","DOIUrl":"10.2214/AJR.24.31675","url":null,"abstract":"<p><p><b>BACKGROUND.</b> Tumor growth processes result in spatial heterogeneity, with the development of tumor subregions (i.e., habitats) having unique biologic characteristics. <b>OBJECTIVE.</b> The purpose of our study was to develop and validate a habitat model combining tumor and peritumoral radiomic features on chest CT for predicting invasiveness of lung adenocarcinoma. <b>METHODS.</b> This retrospective study included 1156 patients (mean age, 57.5 years; 464 men, 692 women), from three centers and a public dataset, who underwent chest CT before lung adenocarcinoma resection (variable date ranges across datasets). Patients from one center formed training (<i>n</i> = 500) and validation (<i>n</i> = 215) sets; patients from the other sources formed three external test sets (<i>n</i> = 249, 113, 79). For each patient, a single nodule was manually segmented on chest CT. The nodule segmentation was combined with an automatically generated 4-mm peritumoral region into a whole-volume volume of interest (VOI). A gaussian mixture model (GMM) identified voxel clusters with similar first-order energy across patients. GMM results were used to divide each patient's whole-volume VOI into multiple habitats, which were defined consistently across patients. Radiomic features were extracted from each habitat. After feature selection, a habitat model was developed for predicting invasiveness, with the use of pathologic assessment as a reference. An integrated model was constructed, combining features extracted from habitats and whole-volume VOIs. Model performance was evaluated, including in subgroups based on nodule density (pure ground-glass, part-solid, and solid). The code for habitat imaging and model construction is publicly available (https://github.com/Shangyoulan/Habitat/). <b>RESULTS.</b> Invasive cancer was diagnosed in 626 of 1156 patients. GMM identified four as the optimal number of voxel clusters and thus of per-patient tumor habitats. The habitat model had an AUC of 0.932 in the validation set and 0.881, 0.880, and 0.764 in the three external test sets. The integrated model had an AUC of 0.947 in the validation set and 0.936, 0.908, and 0.800 in the three external test sets. In the three external test sets combined, across nodule densities, AUCs for the habitat model were 0.836-0.869 and for the integrated model were 0.846-0.917. <b>CONCLUSION.</b> Habitat imaging combining tumoral and peritumoral radiomic features could help predict lung adenocarcinoma invasiveness. Prediction is improved when combining information on tumor subregions and the tumor overall. <b>CLINICAL IMPACT.</b> The findings may aid personalized preoperative assessments to guide clinical decision-making in lung adenocarcinoma.</p>","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141977287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reply to: \"Optimizing Cryoablation for Breast Cancer: Proposals for Extended Follow-Up and Methodologic Enhancements\".","authors":"Karim Oueidat, Robert C Ward","doi":"10.2214/AJR.24.32013","DOIUrl":"10.2214/AJR.24.32013","url":null,"abstract":"","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142301763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mitigating Misses and Misinterpretations: <i>AJR</i> Podcast Series on Diagnostic Excellence and Error, Episode 4.","authors":"Francis Deng, David M Yousem","doi":"10.2214/AJR.24.32081","DOIUrl":"10.2214/AJR.24.32081","url":null,"abstract":"","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142333031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond the <i>AJR</i>: Can Prostate MRI and MRI-Guided Biopsy Be Cost-Effective in the United States in Patients With Elevated PSA?","authors":"Francesco Giganti, Rajan T Gupta","doi":"10.2214/AJR.24.30973","DOIUrl":"10.2214/AJR.24.30973","url":null,"abstract":"","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139731075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial Comment: Unveiling Tumor Heterogeneity-Habitat-Based Radiomics for Lung Adenocarcinoma.","authors":"Xiaodong Zhang","doi":"10.2214/AJR.24.31944","DOIUrl":"10.2214/AJR.24.31944","url":null,"abstract":"","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142082707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Global Reading Room: Performing a Core Needle Breast Biopsy.","authors":"Jay A Baker, Almir G V Bitencourt, Norran Hussein Said, Kardinah Kardinah","doi":"10.2214/AJR.23.30721","DOIUrl":"10.2214/AJR.23.30721","url":null,"abstract":"","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139089505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Translational Medicine of 2030: Bedside to Biosphere.","authors":"Reed A Omary, Thomas M Grist","doi":"10.2214/AJR.24.31562","DOIUrl":"10.2214/AJR.24.31562","url":null,"abstract":"<p><p>For more than 2 decades, translational medicine has accelerated basic science discovery into clinical application using a bench-to-bedside framework. Given that climate change represents the single greatest health threat facing humanity, the authors propose extending this framework to now include the bedside to the biosphere. Several potential opportunities in clinical operations, research, and advocacy associated with the use of this framework are provided. In addition, we propose that technology assessment studies of diagnostic imaging measure planetary outcomes alongside patient outcomes.</p>","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141899049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial Comment: Does Burnout Compute? From Measuring a Phenomenon to Invoking Healthy Changes.","authors":"Ingolf Karst","doi":"10.2214/AJR.24.31848","DOIUrl":"10.2214/AJR.24.31848","url":null,"abstract":"","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142127465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Best Practices: Burnout Is More Than Binary.","authors":"Nitya L Thakore, Michael Lan, Abigail Ford Winkel, Dorice L Vieira, Stella K Kang","doi":"10.2214/AJR.24.31111","DOIUrl":"10.2214/AJR.24.31111","url":null,"abstract":"<p><p>Burnout among radiologists is increasingly prevalent, with the potential for having a substantial negative impact on physician well-being, delivery of care, and health outcomes. To evaluate this phenomenon using reliable and accurate means, validated quantitative instruments are essential. Variation in measurement can contribute to wide-ranging findings. This article evaluates radiologist burnout rates globally and dimensions of burnout as reported using different validated instruments; it also provides guidance on best practices to characterize burnout. Fifty-seven studies published between 1990 and 2023 were included in a systematic review, and 43 studies were included in a meta-analysis of burnout prevalence using random-effects models. The reported burnout prevalence ranged from 5% to 85%. With the Maslach Burnout Inventory (MBI), burnout prevalence varied significantly depending on the instrument version used. Among MBI subcategories, the pooled prevalence of emotional exhaustion was 54% (95% CI, 45-63%), depersonalization was 52% (95% CI, 41-63%), and low personal accomplishment was 36% (95% CI, 27-47%). Other validated burnout instruments showed less heterogeneous results; studies using the Stanford Professional Fulfillment Index yielded a burnout prevalence of 39% (95% CI, 34-45%), whereas the validated single-item instrument yielded a burnout prevalence of 34% (95% CI, 29-39%). Standardized instruments for assessing prevalence alongside multidimensional profiles capturing experiences may better characterize radiologist burnout, including change occurring over time.</p>","PeriodicalId":55529,"journal":{"name":"American Journal of Roentgenology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141629341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}