7 research outputs found

    Consequences of intermodality registration errors for intramodality 3D ultrasound IGRT

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    Intramodality ultrasound image-guided radiotherapy systems compare daily ultrasound to reference ultrasound images. Nevertheless, because the actual treatment planning is based on a reference computed tomography image, and not on a reference ultrasound image, their accuracy depends partially on the correct intermodality registration of the reference ultrasound and computed tomography images for treatment planning. The error propagation in daily patient positioning due to potential registration errors at the planning stage was assessed in this work. Five different scenarios were simulated involving shifts or rotations of ultrasound or computed tomography images. The consequences of several workflow procedures were tested with a phantom setup. As long as the reference ultrasound and computed tomography images are made to match, the patient will be in the correct treatment position. In an example with a phantom measurement, the accuracy of the performed manual fusion was found to be ≤2 mm. In clinical practice, manual registration of patient images is expected to be more difficult. Uncorrected mismatches will lead to a systematically incorrect final patient position because there will be no indication that there was a misregistration between the computed tomography and reference ultrasound images. In the treatment room, the fusion with the computed tomography image will not be visible and based on the ultrasound images the patient position seems correct

    Patient-accessible electronic health records:a qualitative study from the perspective of potential users in the Netherlands

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    The Dutch patient-accessible electronic health record (PAEHR) has recently been implemented on a small scale. Yet, little is known about the users’ needs. This study aimed to provide a detailed insight of success and failure factors of the PAEHR. Forty-three citizens and 23 healthcare professionals (HCPs) participated. Audio recordings were transcribed. Open coding was used and codes were put into themes by using NVIVO12. PAEHR leads to more patient-centred care and a more detailed insight into patients’ own health status. The barrier identified was the increased workload of HCPs. Citizens stated that there should be more publicity regarding the PAEHR. Citizens like to receive support from their HCP about the PAEHR, but in contrast, HCPs stated that it is not their task to give instructions. The Dutch government needs to think about appropriate strategies to inform their inhabitants and encourage them and their HCPs to implement the PAEHR successfully

    Development and validation of a patient decision aid for prostate Cancer therapy:from paternalistic towards participative shared decision making

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    Background: Patient decision aids (PDAs) can support the treatment decision making process and empower patients to take a proactive role in their treatment pathway while using a shared decision-making (SDM) approach making participatory medicine possible. The aim of this study was to develop a PDA for prostate cancer that is accurate and user-friendly. Methods: We followed a user-centered design process consisting of five rounds of semi-structured interviews and usability surveys with topics such as informational/decisional needs of users and requirements for PDAs. Our userbase consisted of 8 urologists, 4 radiation oncologists, 2 oncology nurses, 8 general practitioners, 19 former prostate cancer patients, 4 usability experts and 11 healthy volunteers. Results: Informational needs for patients centered on three key factors: treatment experience, post-treatment quality of life, and the impact of side effects. Patients and clinicians valued a PDA that presents balanced information on these factors through simple understandable language and visual aids. Usability questionnaires revealed that patients were more satisfied overall with the PDA than clinicians; however, both groups had concerns that the PDA might lengthen consultation times (42 and 41%, respectively). The PDA is accessible on http://beslissamen.nl/. Conclusions: User-centered design provided valuable insights into PDA requirements but challenges in integrating diverse perspectives as clinicians focus on clinical outcomes while patients also consider quality of life. Nevertheless, it is crucial to involve a broad base of clinical users in order to better understand the decision-making process and to develop a PDA that is accurate, usable, and acceptable

    Development and external validation of multivariate prediction models for erectile dysfunction in men with localized prostate cancer.

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    While the 10-year survival rate for localized prostate cancer patients is very good (>98%), side effects of treatment may limit quality of life significantly. Erectile dysfunction (ED) is a common burden associated with increasing age as well as prostate cancer treatment. Although many studies have investigated the factors affecting erectile dysfunction (ED) after prostate cancer treatment, only limited studies have investigated whether ED can be predicted before the start of treatment. The advent of machine learning (ML) based prediction tools in oncology offers a promising approach to improve the accuracy of prediction and quality of care. Predicting ED may help aid shared decision-making by making the advantages and disadvantages of certain treatments clear, so that a tailored treatment for an individual patient can be chosen. This study aimed to predict ED at 1-year and 2-year post-diagnosis based on patient demographics, clinical data and patient-reported outcomes (PROMs) measured at diagnosis. We used a subset of the ProZIB dataset collected by the Netherlands Comprehensive Cancer Organization (Integraal Kankercentrum Nederland; IKNL) that contained information on 964 localized prostate cancer cases from 69 Dutch hospitals for model training and external validation. Two models were generated using a logistic regression algorithm coupled with Recursive Feature Elimination (RFE). The first predicted ED 1 year post-diagnosis and required 10 pre-treatment variables; the second predicted ED 2 years post-diagnosis with 9 pre-treatment variables. The validation AUCs were 0.84 and 0.81 for 1 year and 2 years post-diagnosis respectively. To immediately allow patients and clinicians to use these models in the clinical decision-making process, nomograms were generated. In conclusion, we successfully developed and validated two models that predicted ED in patients with localized prostate cancer. These models will allow physicians and patients alike to make informed evidence-based decisions about the most suitable treatment with quality of life in mind

    Development and validation of a patient decision aid for prostate Cancer therapy: from paternalistic towards participative shared decision making

    No full text
    Background: Patient decision aids (PDAs) can support the treatment decision making process and empower patients to take a proactive role in their treatment pathway while using a shared decision-making (SDM) approach making participatory medicine possible. The aim of this study was to develop a PDA for prostate cancer that is accurate and user-friendly. Methods: We followed a user-centered design process consisting of five rounds of semi-structured interviews and usability surveys with topics such as informational/decisional needs of users and requirements for PDAs. Our userbase consisted of 8 urologists, 4 radiation oncologists, 2 oncology nurses, 8 general practitioners, 19 former prostate cancer patients, 4 usability experts and 11 healthy volunteers. Results: Informational needs for patients centered on three key factors: treatment experience, post-treatment quality of life, and the impact of side effects. Patients and clinicians valued a PDA that presents balanced information on these factors through simple understandable language and visual aids. Usability questionnaires revealed that patients were more satisfied overall with the PDA than clinicians; however, both groups had concerns that the PDA might lengthen consultation times (42 and 41%, respectively). The PDA is accessible on http://beslissamen.nl/. Conclusions: User-centered design provided valuable insights into PDA requirements but challenges in integrating diverse perspectives as clinicians focus on clinical outcomes while patients also consider quality of life. Nevertheless, it is crucial to involve a broad base of clinical users in order to better understand the decision-making process and to develop a PDA that is accurate, usable, and acceptable
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