Health Research with Data in a Time of Privacy: Which Information do Patients Want?

When hospitals ask broad consent for the secondary use of patient data for scientific research, it is unknown for which studies the data will be used. We investigated what patients at a cancer hospital consider to be an adequate level and most suitable method of information provision using questionnaires (n = 71) and interviews (n = 24). A part of the respondents indicated that they would feel sufficiently informed by either being notified about potential further use, or by receiving a general brochure before being asked for consent. Others stated that additional information would be interesting and appreciated. Yet, when discussing required resources needed to provide additional information, interviewees lowered the bar of what they considered minimally required, voicing the importance of spending resources on research.

Take Action Protocol: A radiation therapist led approach to act on anatomical changes seen on CBCT.

Until recently Traffic Light Protocols (TLP) have been developed to recognize and react to Anatomical Changes (ACs) seen on Cone Beam Computer Tomography (CBCT) scans for the most common treatment sites. This involves alerting the Radiation Oncologist (RO), handing over findings, and RO providing the final decision, making it quite labour-intensive for the ROs as well as the Radiation Therapists (RTTs). A new approach was developed to act on ACs: the Take Action Protocol (TAP). In this protocol the RTTs do not only have a role in detecting ACs, but also decide on the appropriate action and follow up, resulting in a significant shift in responsibility. In this study we present the TAP and evaluated the benefit and outcomes of the implementation of TAP compared to the TLP. During a pilot period of six months the TAP was applied for 34 bladder and prostate patients. In 2 bladder and 6 prostate patients further decision making by an RO was required (compared to all 34 in the TLP), showing a large reduction in workload. ACs were accurately assessed by RTTs in >99% of the cases. In 5/34 patients RTTs specialized in Image Guided Radiotherapy provided additional instructions to improve accurate use of the TAP. Two surveys conducted by both ROs and RTTs on the TLP and TAP showed that the perceived involvement of the ROs and burden of responsibility for RTTs was comparable between the two protocols. The identification of patients with truly clinical relevant ACs and the adaptation of treatment for the remaining fractions improved according to ROs and RTTs responses. The TAP provides a better balance between workload and efficiency in relation to the clinical relevance of acting on ACs.

An anomaly detector as a clinical decision support system for parotid gland delineations.

Purpose. Auto-contouring (AC) is rapidly becoming standard practice for OAR contouring. However, in clinical practice, clinicians still need to manually check and correct contours. Anomaly detection systems (ADS) can aid the clinical decision process by suggesting which structures require corrections or not, greatly enhancing the value of AC. The purpose of this work is to develop and evaluate a decision support system for detecting anomalies in the case of parotid gland delineations. METHODS: Head and neck parotid gland delineations (1037 right, 1038 left), were retrieved from the Netherlands Cancer Institute (NKI) database. Morphological and image-based features were extracted from each patient's CT and structure set. An isolation forest model was initially trained on 70% of the data, of which 10% had synthetically generated anomalies and validated on the remaining 30% of clinical data. The ADS was tested on an independent set of 250 patients (Normal: 174, Anomalies: 76) and on a clinical autocontouring software. RESULTS: Applied to the validation set, the ADS system resulted in area under the curve (AUC) values of 0.93 and 0.94 for the parotid left and right respectively. Image features appeared more important than morphological, but using all features resulted marginally in the best model. Applied to the test set the ADS system reached an accuracy level of 0.83 and 0.81 for the parotid left and right respectively. The ADS was particularly sensitive to uniform expansions/contractions, misplacements, extra/missing slices and anisotropic over-contouring. CONCLUSION: Anomaly detection can serve as a powerful contour quality assurance tool, especially for cases of organ misplacement and over-contouring.

Factors predicting timely implementation of radiotherapy innovations: the first model.

OBJECTIVE: The improvement of radiotherapy depends largely on the implementation of innovations, of which effectivity varies widely. The aim of this study is to develop a prediction model for successful innovation implementation in radiotherapy to improve effective management of innovation projects. METHODS: A literature review was performed to identify success factors for innovation implementation. Subsequently, in two large academic radiotherapy centres in the Netherlands, an inventory was made of all innovation projects executed between 2011 and 2017. Semi-structured interviews were performed to record the presence/absence of the success factors found in the review for each project. Successful implementation was defined as timely implementation, yes/no. Cross-tables, Χ2 tests, t-tests and Benjamin-Hochberg correction were used for analysing the data. A multivariate logistic regression technique was used to build a prediction model. RESULTS: From the 163 identified innovation projects, only 54% were successfully implemented. We found 31 success factors in literature of which 14 were significantly related to successful implementation in the innovation projects in our study. The prediction model contained the following determinants: (1) sufficient and competent employees, (2) complexity, (3) understanding/awareness of the project goals and process by employees, (4) feasibility and desirability. The area Under the curve (AUC) of the prediction model was 0.86 (0.8-0.92, 95% CI). CONCLUSION: A prediction model was developed for successful implementation of innovation in radiotherapy. ADVANCES IN KNOWLEDGE: This prediction model is the first of its kind and, after external validation, could be widely applicable to predict the timely implementation of radiotherapy innovations.

Feasibility and accuracy of quantitative imaging on a 1.5 T MR-linear accelerator.

PURPOSE: Systems for magnetic resonance (MR-) guided radiotherapy enable daily MR imaging of cancer patients during treatment, which is of interest for treatment response monitoring and biomarker discovery using quantitative MRI (qMRI). Here, the performance of a 1.5 T MR-linac regarding qMRI was assessed on phantoms. Additionally, we show the feasibility of qMRI in a prostate cancer patient on this system for the first time. MATERIALS AND METHODS: Four 1.5 T MR-linac systems from four institutes were included in this study. T1 and T2 relaxation times, and apparent diffusion coefficient (ADC) maps, as well as dynamic contrast enhanced (DCE) images were acquired. Bland-Altman statistics were used, and accuracy, repeatability, and reproducibility were determined. RESULTS: Median accuracy for T1 ranged over the four systems from 2.7 to 14.3%, for T2 from 10.4 to 14.1%, and for ADC from 1.9 to 2.7%. For DCE images, the accuracy ranged from 12.8 to 35.8% for a gadolinium concentration of 0.5 mM and deteriorated for higher concentrations. Median short-term repeatability for T1 ranged from 0.6 to 5.1%, for T2 from 0.4 to 1.2%, and for ADC from 1.3 to 2.2%. DCE acquisitions showed a coefficient of variation of 0.1-0.6% in the signal intensity. Long-term repeatability was 1.8% for T1, 1.4% for T2, 1.7% for ADC, and 17.9% for DCE. Reproducibility was 11.2% for T1, 2.9% for T2, 2.2% for ADC, and 18.4% for DCE. CONCLUSION: These results indicate that qMRI on the Unity MR-linac is feasible, accurate, and repeatable which is promising for treatment response monitoring and treatment plan adaptation based on daily qMRI.

Substantial Volume Changes and Plan Adaptations During Preoperative Radiation Therapy in Extremity Soft Tissue Sarcoma Patients.

PURPOSE: Many authors suggest that extremity soft tissue sarcomas (ESTS) do not change significantly in size during preoperative radiation therapy (RT). This cone beam computed tomography study investigates the justification to deliver the entire course with 1 initial RT plan by observing anatomic changes during RT. METHODS AND MATERIALS: Between 2015 and 2017, 99 patients with ESTS were treated with either curative (n = 80) or palliative intent (n = 19) with a regimen of at least 6 fractions. The clinical target volume to planning target volume margin was 1 cm. Action levels were assigned by radiation technicians. An extremity contour change of >1 cm and/or tumor size change >0.5 cm required a physician's action before the next fraction. RESULTS: A total of 982 cone beam computed tomography logfiles were studied. In 41 of 99 patients, the dose coverage of the initial treatment plan was fully satisfactory throughout the RT course. However, action levels were observed in 58 patients (59%). In 41 of these 58 patients, a contour increase of 5 to 23 mm was noted (29 tumor size increase only, 3 extremity contour increase, and 9 both). In 21 of 58 patients, a decrease of 5 to 33 mm was observed (20 tumor size decrease only and 1 tumor size decrease and extremity contour decrease). In 4 cases, contours initially increased and subsequently decreased. In 33 of 41 patients with increasing contours, the dose distribution adequately covered gross tumor volume because of the 1 cm planning target volume margin applied. For the remaining 8 patients (8%), the plan needed to be adapted. CONCLUSIONS: ESTS volumes may change substantially during RT in 59% of all patients, leading to plan adaptations resulting from increased volumes in 8%. Daily critical observation of these patients is mandatory to avoid geographic misses because of increases in size and overdosing of normal tissues when masses shrink.