Browsing by Author "Segars, William Paul"

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    Patient-Informed Organ Dose Estimation in Clinical CT: Implementation and Effective Dose Assessment in 1048 Clinical Patients.
    (AJR. American journal of roentgenology, 2021-01-21) Fu, Wanyi; Ria, Francesco; Segars, William Paul; Choudhury, Kingshuk Roy; Wilson, Joshua M; Kapadia, Anuj J; Samei, Ehsan
    OBJECTIVE. The purpose of this study is to comprehensively implement a patient-informed organ dose monitoring framework for clinical CT and compare the effective dose (ED) according to the patient-informed organ dose with ED according to the dose-length product (DLP) in 1048 patients. MATERIALS AND METHODS. Organ doses for a given examination are computed by matching the topogram to a computational phantom from a library of anthropomorphic phantoms and scaling the fixed tube current dose coefficients by the examination volume CT dose index (CTDIvol) and the tube-current modulation using a previously validated convolution-based technique. In this study, the library was expanded to 58 adult, 56 pediatric, five pregnant, and 12 International Commission on Radiological Protection (ICRP) reference models, and the technique was extended to include multiple protocols, a bias correction, and uncertainty estimates. The method was implemented in a clinical monitoring system to estimate organ dose and organ dose-based ED for 647 abdomen-pelvis and 401 chest examinations, which were compared with DLP-based ED using a t test. RESULTS. For the majority of the organs, the maximum errors in organ dose estimation were 18% and 8%, averaged across all protocols, without and with bias correction, respectively. For the patient examinations, DLP-based ED was significantly different from organ dose-based ED by as much as 190.9% and 234.7% for chest and abdomen-pelvis scans, respectively (mean, 9.0% and 24.3%). The differences were statistically significant (p < .001) and exhibited overestimation for larger-sized patients and underestimation for smaller-sized patients. CONCLUSION. A patient-informed organ dose estimation framework was comprehensively implemented applicable to clinical imaging of adult, pediatric, and pregnant patients. Compared with organ dose-based ED, DLP-based ED may overestimate effective dose for larger-sized patients and underestimate it for smaller-sized patients.
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    Virtual imaging trials in medicine: A brief takeaway of the lessons from the first international summit.
    (Medical physics, 2024-12) Samei, Ehsan; Abadi, Ehsan; Bakic, Predrag; Bliznakova, Kristina; Bosmans, Hilde; Carton, Ann-Katherine; Frangi, Alejandro F; Glick, Stephen; Lo, Joseph Y; Kinahan, Paul; Maidment, Andrew; Ria, Francesco; Sechopoulos, Ioannis; Segars, William Paul; Tanaka, Rie; Vancoillie, Liesbeth

    Background

    The rapid advancement of medical technologies presents significant challenges for researchers and practitioners. While traditional clinical trials remain the gold standard, they are often limited by high costs, lengthy durations, and ethical constraints. In contrast, in-silico trials and digital twins have emerged not only as efficient and ethical alternatives but also as a complementary technology that can extend beyond classical trials to predict and design new strategies. The successful application of digital twins in industries like nuclear energy, automotive engineering, and aviation underscores their potential in human health.

    Methods

    In April 2024, Duke University hosted the first international summit on Virtual Imaging Trials in Medicine (VITM). The summit brought together over 130 experts from academia, industry, and regulatory bodies to discuss the latest developments, challenges, and future directions in this field. The event featured plenary speakers, presentations, and panel discussions, emphasizing the integration of clinical and in-silico methods to enhance medical evaluations.

    Results

    Key takeaways included the necessity of diverse and realistic digital patient representations, the integration of physics and biology in simulations, and the development of robust validation frameworks. The summit also highlighted the importance of regulatory science and the establishment of Good Simulation Practices to ensure the credibility and reliability of virtual trials.

    Conclusion

    The key discussions and insights from the VITM summit underscore the potential of in-silico trials to revolutionize medical research and patient care through personalized, efficient, and ethical evaluation methods. The collaborative efforts and recommendations from this summit aim to drive future advancements in virtual imaging trials in medicine.