Automated gross tumour volume contour generation for large-scale analysis of early stage lung cancer patients planned with 4D-CT
Affiliation
Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom.Issue Date
2020
Metadata
Show full item recordAbstract
Purpose: Early stage lung cancer patients undergoing stereotactic ablative radiotherapy receive four-dimensional computed tomography (4D-CT) for treatment planning. Often, an internal gross target volume (iGTV), which approximates the motion envelope of a tumour over the breathing cycle, is delineated without defining a gross tumour volume (GTV). However, the GTV volume and shape are important parameters for prognostic and dose modelling, and there is interest in radiomic features extracted from the GTV and surrounding tissue. We demonstrate and validate a method to generate the GTV from an iGTV contour to aid retrospective analysis on routine data. Method: It is possible to reconstruct the geometry of a tumour with knowledge of tumour motion and the motion envelope formed during respiration. To demonstrate this, tumour motion path was estimated with local rigid registration, and the iGTV positioned incrementally at stations along the reverse path. It is shown that tumour volume is the largest set common to the intersection of the iGTV at the different positions, so hence can be derived. This was implemented for 521 lung lesions on 4D-CT. Eleven patients with a GTV delineation performed by a radiation oncologist on a reference phase (50%) were used for validation. The generated GTV was compared to that delineated by expert using distance-to-agreement, volume, and distance between centres of mass. An overall success rate was determined by detecting registration inaccuracy and performing a quality check on the routine iGTV. For successfully generated contours, GTV volume was compared to iGTV volume in a prognostic model for overall survival. Results: For the validation dataset, distance-to-agreement mean (0.79-1.55mm) and standard deviation (0.68-1.51mm) was comparable to expected observer variation. Difference in volume was less than 5cm3 , and average difference in position was 1.21mm. Deviations in shape and position were mainly caused by delineation interpretation differences between iGTV and GTV as opposed to algorithm performance. For the complete dataset, an acceptable contour was generated for 94% of patients using statistical and visual assessment to detect failures. Generated GTV volumes improved prognostic model performance over iGTV volumes. Conclusion: A method to generate a GTV from an iGTV and 4D-CT dataset was developed. This method facilitates data analysis of early stage lung cancer patients treated in the routine setting i.e. data mining, prognostic modelling, and radiomics. Generation failure detection removes the need for visual assessment of all contours, reducing a time-consuming aspect of big-data analysis. Favourable prognostic performance of generated GTV volumes over iGTV ones demonstrates opportunities to use this methodology for future study.Citation
Davey A, van Herk M, Faivre-Finn C, Brown S, McWilliam A. Automated gross tumor volume contour generation for large-scale analysis of early-stage lung cancer patients planned with 4D-CT. Med Phys. 2020.Journal
Medical PhysicsDOI
10.1002/mp.14644PubMed ID
33290579Additional Links
https://dx.doi.org/10.1002/mp.14644Type
ArticleLanguage
enae974a485f413a2113503eed53cd6c53
10.1002/mp.14644
Scopus Count
Collections
Related articles
- Does Motion Assessment With 4-Dimensional Computed Tomographic Imaging for Non-Small Cell Lung Cancer Radiotherapy Improve Target Volume Coverage?
- Authors: Ahmed N, Venkataraman S, Johnson K, Sutherland K, Loewen SK
- Issue date: 2017
- A novel four-dimensional radiotherapy planning strategy from a tumor-tracking beam's eye view.
- Authors: Li G, Cohen P, Xie H, Low D, Li D, Rimner A
- Issue date: 2012 Nov 21
- Feasibility and potential benefits of defining the internal gross tumor volume of hepatocellular carcinoma using contrast-enhanced 4D CT images obtained by deformable registration.
- Authors: Xu H, Gong G, Wei H, Chen L, Chen J, Lu J, Liu T, Zhu J, Yin Y
- Issue date: 2014 Oct 16
- [Comparison of three methods to delineate internal gross target volume of the primary hepatocarcinoma based on four-dimensional CT simulation images].
- Authors: Xing J, Li JB, Zhang YJ, Li FX, Fan TY, Xu M, Shang DP, Han JJ
- Issue date: 2012 Feb
- Determination of patient-specific internal gross tumor volumes for lung cancer using four-dimensional computed tomography.
- Authors: Ezhil M, Vedam S, Balter P, Choi B, Mirkovic D, Starkschall G, Chang JY
- Issue date: 2009 Jan 27