The Impact of Gross Tumor Volume (GTV) and Clinical Target Volume (CTV) Definition on the Total Accuracy in Radiotherapy

Weiss, Elisabeth; Hess, Clemens F.

doi:10.1007/s00066-003-0976-5

Cited by 187 publications

(137 citation statements)

References 36 publications

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“…Intra-observer variation is either in agreement or smaller than inter-observer variation similarly to previously reported clinical findings [5]. Disagreement between the same TPS is evident for contours generated using auto-threshold tools in the same TPS by different observers, (Fig.…”

Section: Discussionsupporting

confidence: 88%

“…Knowledge of these baseline values is important for clinical trials which commonly occur across multiple centres and TPSs. Current literature does not give clear guidelines for reporting contouring variability in inter-observer studies [4] with variation in methodology and metrics only enabling comparison between inter-observer studies in a limited fashion [5]. As such, calculating multiple metrics including a combination of descriptive statistics, overlap measures and statistical measures of agreement is recommended for multiple observer studies [6].…”

Section: Introductionmentioning

confidence: 99%

“…Inadequate definition of the Gross Tumour Volume (GTV) or Clinical Target Volume (CTV) leads to systematic uncertainty which may result in geometric miss of the tumour throughout the course of patient radiation therapy [5]. As such there has been an increasing trend to assess, and reduce, the variability of these target volumes.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A phantom assessment of achievable contouring concordance across multiple treatment planning systems

Pogson

Begg

Jameson

et al. 2015

Radiotherapy and Oncology

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In this paper, the highest level of inter-and intra-observer conformity achievable with different treatment planning systems (TPSs), contouring tools, shapes, and sites have been established for metrics including the Dice similarity coefficient (DICE) 2 AbstractIn this paper, metrics including the Dice similarity coefficient (DICE) and Hausdorff Distance determine the highest level of inter-and intra-observer conformity achievable with different treatment planning systems (TPSs), contouring tools, shapes, and sites. High conformity values, e.g. DICE Breast_Shape =0.99±0.01, are achieved with differing TPSs. Decreasing image resolution decreased contouring conformity.

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Section: Discussionsupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

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A phantom assessment of achievable contouring concordance across multiple treatment planning systems

Pogson

Begg

Jameson

et al. 2015

Radiotherapy and Oncology

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“…In reality, CTV delineation uncertainties exist and should be included in the CTV for a more accurate margin to a better tumor control. Weiss and Hess (17) suggested that interobserver variability in target delineation was a major factor causing treatment inaccuracy. The delineation uncertainty can be reduced by using multimodality imaging as suggested by Rasch et al (18) The overall CTV‐to‐PTV margin, including tumor delineation, setup uncertainties, and internal organ displacement, should be fully investigated before determining PTV margin.…”

Section: Discussionmentioning

confidence: 99%

Estimation of patient setup uncertainty using BrainLAB Exatrac X‐Ray 6D system in image‐guided radiotherapy

Infusino

Trodella

Ramella

et al. 2015

J Applied Clin Med Phys

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The purpose of this study was to evaluate setup uncertainties for brain sites with ExacTrac X‐Ray 6D system and to provide optimal margin guidelines. Fifteen patients with brain tumor were included in this study. Two X‐ray images with ExacTrac X‐Ray 6D system were used to verify patient position and tumor target localization before each treatment. The 6D fusion software first generates various sets of DRRs with position variations in both three translational and three rotational directions (six degrees of freedom) for the CT images. Setup variations (translation and rotation) after correction were recorded and corrected before treatment. The 3D deviations are expressed as mean±standard deviation. The random error false(normalΣfalse(σifalse)false), systematic error false(μifalse), and group systematic error false(Mfalse(μifalse)false) for the different X‐ray were calculated using the definitions of van Herk. (1) Mean setup errors were calculated from X‐ray images acquired after all fractions. There is moderate patient‐to‐patient variation in the vertical direction and small variations in systematic errors and magnitudes of random errors are smaller. The global systematic errors were measured to be less than 2.0 mm in each direction. Random component of all patients are smaller ranging from 0.1–0.3 mm small. The safety margin (SM) to the lateral, is 0.5 mm and 2.6 mm for van Herk (1) and Stroom et al., (2) respectively, craniocaudal axis is 1.5 mm and 3.4 mm, respectively, and with respect to the antero–posterior axis, 2.3 mm and 3.9 mm. Daily X‐ray imaging is essential to compare and assess the accuracy of treatment delivery to different anatomical locations.PACS number: 87.55.D

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“…Delineating treatment targets within DICOM files is complex, operator-dependent, and critical to the accurate delivery of conformal radiotherapy [11][12][13][14][15]. These variabilities in target volume delineation can be a major primary source of inaccuracy of dose delivery and treatment errors [16]. Consequently, efforts have been made to identify processes in the target delineation process amenable to improvement, such as multimodality image incorporation [8,[17][18][19][20][21][22], instructional modification [23][24][25], visual atlas usage [11-15, 26, 27], window-level adjustment [28], autosegmentation [29,30], and software-assisted contouring [25].…”

Section: Discussionmentioning

confidence: 99%

Human–Computer Interaction in Radiotherapy Target Volume Delineation: A Prospective, Multi-institutional Comparison of User Input Devices

et al. 2010

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The purpose of this study was the prospective comparison of objective and subjective effects of target volume region of interest (ROI) delineation using mousekeyboard and pen-tablet user input devices (UIDs). The study was designed as a prospective test/retest sequence, with Wilcoxon signed rank test for matchedpair 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.

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The Impact of Gross Tumor Volume (GTV) and Clinical Target Volume (CTV) Definition on the Total Accuracy in Radiotherapy

Abstract: Consequences to reduce interobserver variability are proposed, among others the selection of adequate imaging modalities, intensified radiologic training, and the use of telecommunication tools.

Cited by 187 publications

References 36 publications

A phantom assessment of achievable contouring concordance across multiple treatment planning systems

A phantom assessment of achievable contouring concordance across multiple treatment planning systems

Estimation of patient setup uncertainty using BrainLAB Exatrac X‐Ray 6D system in image‐guided radiotherapy

Human–Computer Interaction in Radiotherapy Target Volume Delineation: A Prospective, Multi-institutional Comparison of User Input Devices

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