T. Schimek-Jasch

Impact of 4D-18FDG-PET/CT imaging on target volume delineation in SBRT patients with central versus peripheral lung tumors. Multi-reader comparative study

PURPOSE Evaluation of the effect of co-registered 4D-(18)FDG-PET/CT for SBRT target delineation in patients with central versus peripheral lung tumors. METHODS Analysis of internal target volume (ITV) delineation of central and peripheral lung lesions in 21 SBRT-patients. Manual delineation was performed by 4 observers in 2 contouring phases: on respiratory gated 4DCT with diagnostic 3DPET available aside (CT-ITV) and on co-registered 4DPET/CT (PET/CT-ITV). Comparative analysis of volumes and inter-reader agreement. RESULTS 11 cases of peripheral and 10 central lesions were evaluated. In peripheral lesions, average CT-ITV was 6.2 cm(3) and PET/CT-ITV 8.6 cm(3), resembling a mean change in hypothetical radius of 2 mm. For both CT-ITVs and PET/CT-ITVs inter reader agreement was good and unchanged (0.733 and 0.716; p=0.58). All PET/CT-ITVs stayed within the PTVs derived from CT-ITVs. In central lesions, average CT-ITVs were 42.1 cm(3), PET/CT-ITVs 44.2 cm(3), without significant overall volume changes. Inter-reader agreement improved significantly (0.665 and 0.750; p<0.05). 2/10 PET/CT-ITVs exceeded the PTVs derived from CT-ITVs by >1 ml in average for all observers. CONCLUSION The addition of co-registered 4DPET data to 4DCT based target volume delineation for SBRT of centrally located lung tumors increases the inter-observer agreement and may help to avoid geographic misses.

User Interaction in Semi-Automatic Segmentation of Organs at Risk: a Case Study in Radiotherapy

Accurate segmentation of organs at risk is an important step in radiotherapy planning. Manual segmentation being a tedious procedure and prone to inter- and intra-observer variability, there is a growing interest in automated segmentation methods. However, automatic methods frequently fail to provide satisfactory result, and post-processing corrections are often needed. Semi-automatic segmentation methods are designed to overcome these problems by combining physicians’ expertise and computers’ potential. This study evaluates two semi-automatic segmentation methods with different types of user interactions, named the “strokes” and the “contour”, to provide insights into the role and impact of human-computer interaction. Two physicians participated in the experiment. In total, 42 case studies were carried out on five different types of organs at risk. For each case study, both the human-computer interaction process and quality of the segmentation results were measured subjectively and objectively. Furthermore, different measures of the process and the results were correlated. A total of 36 quantifiable and ten non-quantifiable correlations were identified for each type of interaction. Among those pairs of measures, 20 of the contour method and 22 of the strokes method were strongly or moderately correlated, either directly or inversely. Based on those correlated measures, it is concluded that: (1) in the design of semi-automatic segmentation methods, user interactions need to be less cognitively challenging; (2) based on the observed workflows and preferences of physicians, there is a need for flexibility in the interface design; (3) the correlated measures provide insights that can be used in improving user interaction design.

Using a contextualized sensemaking model for interaction design

Sensemaking 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.

Using GOMS and NASA-TLX to Evaluate Human-Computer Interaction Process in Interactive Segmentation

ABSTRACT HCI plays an important role in interactive medical image segmentation. The Goals, Operators, Methods, and Selection rules (GOMS) model and the National Aeronautics and Space Administration Task Load Index (NASA-TLX) questionnaire are different methods that are often used to evaluate the HCI process. In this article, we aim at improving the HCI process of interactive segmentation using both the GOMS model and the NASA-TLX questionnaire to: 1) identify the relations between these two methods and 2) propose HCI design suggestions based on the synthesis of the evaluation results using both methods. For this, we conducted an experiment where three physicians used two interactive segmentation approaches to segment different types of organs at risk for radiotherapy planning. Using the GOMS model, we identified 16 operators and 10 methods. Further analysis discovered strong relations between the use of GOMS operators and the results of the NASA-TLX questionnaire. Finally, HCI design issues were identified, and suggestions were proposed based on the evaluation results and the identified relations.

Visualization of 4D multimodal imaging data and its applications in radiotherapy planning

Abstract Purpose To explore the benefit of using 4D multimodal visualization and interaction techniques for defined radiotherapy planning tasks over a treatment planning system used in clinical routine (C‐TPS) without dedicated 4D visualization. Methods We developed a 4D visualization system (4D‐VS) with dedicated rendering and fusion of 4D multimodal imaging data based on a list of requirements developed in collaboration with radiation oncologists. We conducted a user evaluation in which the benefits of our approach were evaluated in comparison to C‐TPS for three specific tasks: assessment of internal target volume (ITV) delineation, classification of tumor location in peripheral or central, and assessment of dose distribution. For all three tasks, we presented test cases for which we measured correctness, certainty, consistency followed by an additional survey regarding specific visualization features. Results Lower quality of the test ITVs (ground truth quality was available) was more likely to be detected using 4D‐VS. ITV ratings were more consistent in 4D‐VS and the classification of tumor location had a higher accuracy. Overall evaluation of the survey indicates 4D‐VS provides better spatial comprehensibility and simplifies the tasks which were performed during testing. Conclusions The use of 4D‐VS has improved the assessment of ITV delineations and classification of tumor location. The visualization features of 4D‐VS have been identified as helpful for the assessment of dose distribution during user testing.

EP-1862: Impact of 4DPET/CT on normal tissue sparing for SBRT of central lung tumors

ESTRO 35 2016 _____________________________________________________________________________________________________ cm amplitude. A Fourier Transform (FT) was used to calculate the MTF of the images for the static and moving phantom. The MTF of five commonly used LOG filters were calculated. The response of the filters was compared with the MTF of the images to determine if the motion would affect the response of the filter.

PD-0429: Multireader study on 4DPET/CT target volume delineation in SBRT patients with central versus peripheral lung tumors

ACEi/ARBs users vs. non-users (5.3% vs. 5.3%, p = 1.000). On univariate analysis, higher V20 (p = 0.00071), centrally located tumors (p = 0.00025), and higher baseline FEV1 percentage (p = 0.03577) were associated with increased incidence of RP. On multivariate analysis, both higher V20 (p <0.0001) and centrally located tumors (p = 0.0094) were associated with increased incidence of RP. There was no identifiable relationship between age, gender, ethnicity, BMI, KPS, Charlson comorbidity score, smoking status or history, chemotherapy prior to or post SBRT, baseline DLCO, and total radiation dose or fractionation with the incidence of RP. Conclusions: The use of ACEi/ARBs at the time of lung SBRT did not demonstrate a significant association with the incidence of symptomatic RP despite previously reported data suggesting the opposite. Higher V20’s and centrally located tumors, however, were associated with increased incidence of RP. Given conflicting data of the protective effects an ACEi/ARBs may have against RP, a prospective evaluation is necessary.