Effect of window level on target volume delineation in treatment planning

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.

The importance of surrounding tissues and window settings for contouring of moving targets

AIM

The aim of the study was to assess the importance of surrounding tissues for the delineation of moving targets in tissue-specific phantoms and to find optimal settings for lung, soft tissue, and liver tumors.

MATERIALS AND METHODS

Tumor movement was simulated by a water-filled table tennis ball (target volume, TV). Three phantoms were created: corkboards to simulate lung tissue (lung phantom, LunPh), animal fat as fatty soft tissue (fatty tissue phantom, FatPh), and water enhanced with contrast medium as the liver tissue (liver phantom, LivPh). Slow planning three-dimensional compute tomography images (3D-CTs) were acquired with and without phantom movements. One-dimensional tumor movement (1D), three-dimensional tumor movement (3D), as well as a real patient's tumor trajectories were simulated. The TV was contoured using two lung window settings, two soft-tissue window settings, and one liver window setting. The volumes were compared to mathematical calculated values.

RESULTS

TVs were underestimated in all phantoms due to movement. The use of soft-tissue windows in the LivPh led to a significant underestimation of the TV (70.8% of calculated TV). When common window settings [LunPh + 200 HU/-1,000 HU (upper window/lower window threshold); FatPh: + 240 HU/-120 HU; LivPh: + 175 HU/+ 50 HU] were used, the contoured TVs were: LivPh, 84.0%; LunPh, 93.2%, and FatPh, 92.8%. The lower window threshold had a significant impact on the size of the delineated TV, whereas changes of the upper threshold led only to small differences.

CONCLUSION

The decisive factor for window settings is the lower window threshold (for adequate TV delineation in the lung and fatty-soft tissue it should be lower than density values of surrounding tissue). The use of a liver window should be considered.

Human-computer interaction in radiotherapy target volume delineation: a prospective, multi-institutional comparison of user input devices

The purpose of this study was the prospective comparison of objective and subjective effects of target volume region of interest (ROI) delineation using mouse-keyboard and pen-tablet user input devices (UIDs). The study was designed as a prospective test/retest sequence, with Wilcoxon signed rank test for matched-pair comparison. Twenty-one physician-observers contoured target volume ROIs on four standardized cases (representative of brain, prostate, lung, and head and neck malignancies) twice: once using QWERTY keyboard/scroll-wheel mouse UID and once with pen-tablet UID (DTX2100, Wacom Technology Corporation, Vancouver, WA, USA). Active task time, ROI manipulation task data, and subjective survey data were collected. One hundred twenty-nine target volume ROI sets were collected, with 62 paired pen-tablet/mouse-keyboard sessions. Active contouring time was reduced using the pen-tablet UID, with mean ± SD active contouring time of 26 ± 23 min, compared with 32 ± 25 with the mouse (p ≤ 0.01). Subjective estimation of time spent was also reduced from 31 ± 26 with mouse to 27 ± 22 min with the pen (p = 0.02). Task analysis showed ROI correction task reduction (p = 0.045) and decreased panning and scrolling tasks (p < 0.01) with the pen-tablet; drawing, window/level changes, and zoom commands were unchanged (p = n.s.) Volumetric analysis demonstrated no detectable differences in ROI volume nor intra- or inter-observer volumetric coverage. Fifty-two of 62 (84%) users preferred the tablet for each contouring task; 5 of 62 (8%) denoted no preference, and 5 of 62 (8%) chose the mouse interface. The pen-tablet UID reduced active contouring time and reduced correction of ROIs, without substantially altering ROI volume/coverage.