Browsing by Subject "Radiography"

Now showing 1 - 5 of 5
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    Comparison of Electrosurgical and Formocresol Pulpotomy Procedures
    (1997) Fulkerson, Bradley Todd; Dean, Jeffrey A.; Avery, David R.; Sanders, Brian J.; Zunt, Susan L.; Legan, Joseph E.
    Formocresol is the most commonly used pharmacologic pulpotomy agent. Concerns over its safety have led investigators to search for new pulpotomy medicaments. This study compared the electrosurgical pulpotomy with the formocresol pulpotomy in teeth requiring pulp therapy after carious involvement. There were 25 pulpotomies performed in each group. The teeth were evaluated for clinical and radiographic success after at least six months. In the electrosurgical group, the clinical and radiographic success rates were 96 percent and 84 percent, respectively. The age range at the time of treatment was 26 to 97 months, with a mean treatment age of 63.6 months. The postoperative observation time range was six to 31 months, with the mean being 10.9 months. In the formocresol group, the clinical and radiographic success rates were 100 percent and 92 percent, respectively. The age range at the time of treatment was 32 to 126 months, with a mean treatment age of 68.2 months. The postoperative observation time ranged from five to 25 months, with the mean being 11.5 months. The electrosurgical and formocresol groups were compared for differences in the percentage of successes by using a Fisher's Exact test. There were no statistical differences between the two groups at the p < 0.05 level. Therefore, this study failed to demonstrate a statistically significant difference in the success rate between the electrosurgical and formocresol pulpotomy techniques and supports the use of the electrosurgical pulpotomy as a viable and safe alternative to formocresol.
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    Mild Anastomotic Stenosis in Patient-Specific CABG Model May Enhance Graft Patency: A New Hypothesis
    (Public Library of Science, 2013-09-13) Huo, Yunlong; Luo, Tong; Guccione, Julius M.; Teague, Shawn D.; Tan, Wenchang; Navia, José A.; Kassab, Ghassan S.; Surgery, School of Medicine
    It is well known that flow patterns at the anastomosis of coronary artery bypass graft (CABG) are complex and may affect the long-term patency. Various attempts at optimal designs of anastomosis have not improved long-term patency. Here, we hypothesize that mild anastomotic stenosis (area stenosis of about 40-60%) may be adaptive to enhance the hemodynamic conditions, which may contribute to slower progression of atherosclerosis. We further hypothesize that proximal/distal sites to the stenosis have converse changes that may be a risk factor for the diffuse expansion of atherosclerosis from the site of stenosis. Twelve (12) patient-specific models with various stenotic degrees were extracted from computed tomography images using a validated segmentation software package. A 3-D finite element model was used to compute flow patterns including wall shear stress (WSS) and its spatial and temporal gradients (WSS gradient, WSSG, and oscillatory shear index, OSI). The flow simulations showed that mild anastomotic stenosis significantly increased WSS (>15 dynes · cm(-2)) and decreased OSI (<0.02) to result in a more uniform distribution of hemodynamic parameters inside anastomosis albeit proximal/distal sites to the stenosis have a decrease of WSS (<4 dynes · cm(-2)). These findings have significant implications for graft adaptation and long-term patency.
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    Negligible therapeutic impact, false-positives, overdiagnosis and lead-time are the reasons why radiographs bring more harm than benefits in the caries diagnosis of preschool children
    (BMC, 2021-03-31) Pontes, Laura Regina A.; Lara, Juan Sebastian; Novaes, Tatiane Fernandes; Gomes Freitas, Julia; Gimenez, Thais; Moro, Bruna Lorena P.; Maia, Haline C. M.; Imparato, José Carlos P.; Braga, Mariana M.; Raggio, Daniela P.; Mendes, Fausto M.; Cariology, Operative Dentistry and Dental Public Health, School of Dentistry
    Background: To evaluate the clinical course and interventions required during two years of follow-up of dental surfaces of deciduous molars diagnosed, and consequently treated, by two different strategies: diagnosis made by clinical examination alone or associated with radiographs. Methods: This is a secondary analysis of a two-arm randomized clinical trial with parallel groups related to the diagnostic strategy for caries detection in preschool children. 216 children (3-6 years old) were followed-up for two years. All dental surfaces were diagnosed by visual inspection and later, through radiographic assessment. Baseline treatment was made in accordance with the results obtained by visual inspection performed alone or combined with radiographic method, considering the allocated group. Dental surfaces with no restoration needs, or those restored at the beginning of the study were followed-up for two years. The treatment decision was made according to the allocated group. The outcome was the occurrence of failure (a new caries lesion or a restoration replacement) during the follow-up. Results: 4383 proximal and occlusal surfaces of deciduous molars in 216 preschool children were diagnosed and treated according to the abovementioned diagnostic strategies and followed-up for 24 months. The assessment of radiographs made change the initial decision reached by visual inspection in about 30% of the surfaces when all types of interventions were considered. However, most disagreements occurred for initial lesions, where radiographs tended to underestimate them. Discordances between methods occurred in less than 5% of all surfaces when considered lesions requiring operative treatment. For discrepancy cases, the placed interventions guided by following the radiographic results did not present less failures against those made following only visual inspection. As a matter of fact, the use of radiographs in the diagnostic strategy for caries detection in children brought more harms than benefits due to the occurrence of false-positives, overdiagnosis and lead-time bias. Conclusions: Simultaneous association of visual inspection and radiographic assessment for caries detection in preschool children causes more harms than benefits, and therefore, visual inspection should be conducted alone in the regular clinical practice. Trial registration Clinicaltrials.gov platform: NCT02078453, registered on 5th March 2014.
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    Preparing a collection of radiology examinations for distribution and retrieval
    (Oxford University Press, 2016-03) Demner-Fushman, Dina; Kohli, Marc D.; Rosenman, Marc B.; Shooshan, Sonya E.; Rodriguez, Laritza; Antani, Sameer; Thoma, George R.; McDonald, Clement J.; Department of Radiology and Imaging Sciences, IU School of Medicine
    OBJECTIVE: Clinical documents made available for secondary use play an increasingly important role in discovery of clinical knowledge, development of research methods, and education. An important step in facilitating secondary use of clinical document collections is easy access to descriptions and samples that represent the content of the collections. This paper presents an approach to developing a collection of radiology examinations, including both the images and radiologist narrative reports, and making them publicly available in a searchable database. MATERIALS AND METHODS: The authors collected 3996 radiology reports from the Indiana Network for Patient Care and 8121 associated images from the hospitals' picture archiving systems. The images and reports were de-identified automatically and then the automatic de-identification was manually verified. The authors coded the key findings of the reports and empirically assessed the benefits of manual coding on retrieval. RESULTS: The automatic de-identification of the narrative was aggressive and achieved 100% precision at the cost of rendering a few findings uninterpretable. Automatic de-identification of images was not quite as perfect. Images for two of 3996 patients (0.05%) showed protected health information. Manual encoding of findings improved retrieval precision. CONCLUSION: Stringent de-identification methods can remove all identifiers from text radiology reports. DICOM de-identification of images does not remove all identifying information and needs special attention to images scanned from film. Adding manual coding to the radiologist narrative reports significantly improved relevancy of the retrieved clinical documents. The de-identified Indiana chest X-ray collection is available for searching and downloading from the National Library of Medicine (http://openi.nlm.nih.gov/).
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    “Shortcuts” Causing Bias in Radiology Artificial Intelligence: Causes, Evaluation, and Mitigation
    (Elsevier, 2023) Banerjee, Imon; Bhattacharjee, Kamanasish; Burns, John L.; Trivedi, Hari; Purkayastha, Saptarshi; Seyyed-Kalantari, Laleh; Patel, Bhavik N.; Rakesh, Shiradkar; Judy, Gichoya; Radiology and Imaging Sciences, School of Medicine
    Despite the expert-level performance of artificial intelligence (AI) models for various medical imaging tasks, real-world performance failures with disparate outputs for various subgroups limit the usefulness of AI in improving patients' lives. Many definitions of fairness have been proposed, with discussions of various tensions that arise in the choice of an appropriate metric to use to evaluate bias; for example, should one aim for individual or group fairness? One central observation is that AI models apply "shortcut learning" whereby spurious features (such as chest tubes and portable radiographic markers on intensive care unit chest radiography) on medical images are used for prediction instead of identifying true pathology. Moreover, AI has been shown to have a remarkable ability to detect protected attributes of age, sex, and race, while the same models demonstrate bias against historically underserved subgroups of age, sex, and race in disease diagnosis. Therefore, an AI model may take shortcut predictions from these correlations and subsequently generate an outcome that is biased toward certain subgroups even when protected attributes are not explicitly used as inputs into the model. As a result, these subgroups became nonprivileged subgroups. In this review, the authors discuss the various types of bias from shortcut learning that may occur at different phases of AI model development, including data bias, modeling bias, and inference bias. The authors thereafter summarize various tool kits that can be used to evaluate and mitigate bias and note that these have largely been applied to nonmedical domains and require more evaluation for medical AI. The authors then summarize current techniques for mitigating bias from preprocessing (data-centric solutions) and during model development (computational solutions) and postprocessing (recalibration of learning). Ongoing legal changes where the use of a biased model will be penalized highlight the necessity of understanding, detecting, and mitigating biases from shortcut learning and will require diverse research teams looking at the whole AI pipeline.