ESTRO-ACROP guideline “target delineation of glioblastomas”

Niyazi, Maximilian; Brada, Michael; Chalmers, Anthony J.; Combs, Stephanie E.; Erridge, Sara; Fiorentino, Alba; Grosu, Anca L.; Lagerwaard, Frank J.; Minniti, Giuseppe; Mirimanoff, René-Olivier; Ricardi, Umberto; Short, Susan; Weber, Damien Charles; Belka, Claus

doi:10.1016/j.radonc.2015.12.003

Cited by 325 publications

(269 citation statements)

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“…On review of among others recently reported ASTRO [7] and ESTRO-ACROP guidelines for glioblastomas [8], it would appear that substantial innovations with respect to radiotherapy approaches such as target definition, fractionation and planning as well as delivery techniques are largely lacking, or at least these innovations do not appear to find their way to current guidelines. From this unsubstantiated observation, the question arises whether these components of modern radiotherapy have been an integral part of past or current trials performed in glioblastoma patients.…”

Section: Introductionmentioning

confidence: 99%

Current status and perspectives of interventional clinical trials for glioblastoma – analysis of ClinicalTrials.gov

et al. 2017

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The records of 208.777 (100%) clinical trials registered at ClinicalTrials.gov were downloaded on the 19th of February 2016. Phase II and III trials including patients with glioblastoma were selected for further classification and analysis. Based on the disease settings, trials were classified into three groups: newly diagnosed glioblastoma, recurrent disease and trials with no differentiation according to disease setting. Furthermore, we categorized trials according to the experimental interventions, the primary sponsor, the source of financial support and trial design elements. Trends were evaluated using the autoregressive integrated moving average model. Two hundred sixteen (0.1%) trials were selected for further analysis. Academic centers (investigator initiated trials) were recorded as primary sponsors in 56.9% of trials, followed by industry 25.9%. Industry was the leading source of monetary support for the selected trials in 44.4%, followed by 25% of trials with primarily academic financial support. The number of newly initiated trials between 2005 and 2015 shows a positive trend, mainly through an increase in phase II trials, whereas phase III trials show a negative trend. The vast majority of trials evaluate forms of different systemic treatments (91.2%). In total, one hundred different molecular entities or biologicals were identified. Of those, 60% were involving drugs specifically designed for central nervous system malignancies. Trials that specifically address radiotherapy, surgery, imaging and other therapeutic or diagnostic methods appear to be rare. Current research in glioblastoma is mainly driven or sponsored by industry, academic medical oncologists and neuro-oncologists, with the majority of trials evaluating forms of systemic therapies. Few trials reach phase III. Imaging, radiation therapy and surgical procedures are underrepresented in current trials portfolios. Optimization in research portfolio for glioblastoma is needed.Electronic supplementary materialThe online version of this article (doi:10.1186/s13014-016-0740-5) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

Current status and perspectives of interventional clinical trials for glioblastoma – analysis of ClinicalTrials.gov

et al. 2017

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“…For instance, we observed a mean shape variation (measured by BMHD) decrease by 0.2-0.5 mm. In the treatment plan of GBM, the recommended margin to encompass possible treatment delivery uncertainties is between 3 and 5 mm, depending on the specific situation (Niyazi et al 2016). Such margins are used to compensate the uncertainties in the GTV contouring as well as for shifts in patient positioning.…”

Section: Inter-observer Variation Among Outcomesmentioning

confidence: 99%

The influence of automation on tumor contouring

et al. 2017

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Fully or semi-automatic contouring tools are increasingly being used in the tumor contouring task for radiotherapy. While the fully automatic contouring tools have not reached sufficient efficiency, the semi-automatic contouring tools balance more effectively between the human interaction and automation. This study evaluates the influences of a semi-automation contouring tool, called between-slice interpolation, on the resulting contours and the contouring process. The tumor contouring study was conducted on three patient cases with five physicians in a naturalistic setting. The contouring task consisted of initiating the 2D contour manually or with the interpolation tool and correcting that initial contour. The similarity of the resulting contours was pairwise measured within the manual or the interpolated category. Interactions with the software were recorded, and variations in the contouring workflows steps were compared. Results indicated that using the between-slice interpolation tool for creating the initial contour, instead of initiating it manually, influenced both the contouring process and outcomes. First, it was identified that contours initiated by the interpolation tool showed an increased similarity among themselves compared to the manually initiated contours. At the same time, influences to the resulting contours were below clinical relevance, and toward the desired direction-improved consistency of contours. Second, when interpolation was used, in two cases out of three, the average contouring time also decreased significantly. Therefore, the use of such an automation tool can be encouraged.

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“…This was in accordance to the European Organization for Research and Treatment of Cancer (EORTC) guideline, which states that ''GTV delineation should be based on the resection cavity (if present) plus any residual enhancing tumor on contrast-enhanced T1 weighted MRI, without inclusion of peri-tumoural edema" [36]. Three patient datasets were chosen for the study.…”

Section: Participants and The Setup Of The Studymentioning

confidence: 99%

Using a contextualized sensemaking model for interaction design: A case study of tumor contouring

Aselmaa

Herk

Laprie

et al. 2017

Journal of Biomedical Informatics

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a b s t r a c tSensemaking theories help designers understand the cognitive processes of a user when he/she performs a complicated task. This paper introduces a two-step approach of incorporating sensemaking support within the design of health information systems by: (1) modeling the sensemaking process of physicians while performing a task, and (2) identifying software interaction design requirements that support sensemaking based on this model. The two-step approach is presented based on a case study of the tumor contouring clinical task for radiotherapy planning. In the first step of the approach, a contextualized sensemaking model was developed to describe the sensemaking process based on the goal, the workflow and the context of the task. In the second step, based on a research software prototype, an experiment was conducted where three contouring tasks were performed by eight physicians respectively. Four types of navigation interactions and five types of interaction sequence patterns were identified by analyzing the gathered interaction log data from those twenty-four cases. Further in-depth study on each of the navigation interactions and interaction sequence patterns in relation to the contextualized sensemaking model revealed five main areas for design improvements to increase sensemaking support. Outcomes of the case study indicate that the proposed two-step approach was beneficial for gaining a deeper understanding of the sensemaking process during the task, as well as for identifying design requirements for better sensemaking support.

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ESTRO-ACROP guideline “target delineation of glioblastomas”

Cited by 325 publications

References 50 publications

Current status and perspectives of interventional clinical trials for glioblastoma – analysis of ClinicalTrials.gov

Current status and perspectives of interventional clinical trials for glioblastoma – analysis of ClinicalTrials.gov

The influence of automation on tumor contouring

Using a contextualized sensemaking model for interaction design: A case study of tumor contouring

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