Tumour Auto-contouring on 2d Cine MRI for Locally Advanced Lung Cancer: A Comparative Study

Overview

Journal Radiother Oncol

Specialties Oncology
Radiology

Date 2017 Oct 15

PMID 29029832

Citations 11

Authors

Martin F Fast

Bjorn Eiben

Martin J Menten

Andreas Wetscherek

David J Hawkes

Jamie R McClelland

Uwe Oelfke

Affiliations

Soon will be listed here.

Abstract

Background And Purpose: Radiotherapy guidance based on magnetic resonance imaging (MRI) is currently becoming a clinical reality. Fast 2d cine MRI sequences are expected to increase the precision of radiation delivery by facilitating tumour delineation during treatment. This study compares four auto-contouring algorithms for the task of delineating the primary tumour in six locally advanced (LA) lung cancer patients.

Material And Methods: Twenty-two cine MRI sequences were acquired using either a balanced steady-state free precession or a spoiled gradient echo imaging technique. Contours derived by the auto-contouring algorithms were compared against manual reference contours. A selection of eight image data sets was also used to assess the inter-observer delineation uncertainty.

Results: Algorithmically derived contours agreed well with the manual reference contours (median Dice similarity index: ⩾0.91). Multi-template matching and deformable image registration performed significantly better than feature-driven registration and the pulse-coupled neural network (PCNN). Neither MRI sequence nor image orientation was a conclusive predictor for algorithmic performance. Motion significantly degraded the performance of the PCNN. The inter-observer variability was of the same order of magnitude as the algorithmic performance.

Conclusion: Auto-contouring of tumours on cine MRI is feasible in LA lung cancer patients. Despite large variations in implementation complexity, the different algorithms all have relatively similar performance.

Citing Articles

Respiratory motion modelling for MR-guided lung cancer radiotherapy: model development and geometric accuracy evaluation.

Eiben B, Bertholet J, Tran E, Wetscherek A, Shiarli A, Nill S Phys Med Biol. 2024; 69(5).

PMID: 38266298 PMC: 10875968. DOI: 10.1088/1361-6560/ad222f.

Dosimetry impact of distinct gating strategies in cine MR image-guided breath-hold pancreatic cancer radiotherapy.

Dong Y, Hu P, Li X, Liu W, Yan B, Yang F J Appl Clin Med Phys. 2023; 24(10):e14078.

PMID: 37335543 PMC: 10562039. DOI: 10.1002/acm2.14078.

Accuracy of deformable image registration-based intra-fraction motion management in Magnetic Resonance-guided radiotherapy.

Palacios M, Gerganov G, Cobussen P, Tetar S, Finazzi T, Slotman B Phys Imaging Radiat Oncol. 2023; 26:100437.

PMID: 37089906 PMC: 10113900. DOI: 10.1016/j.phro.2023.100437.

Emergence of MR-Linac in Radiation Oncology: Successes and Challenges of Riding on the MRgRT Bandwagon.

Das I, Yadav P, Mittal B J Clin Med. 2022; 11(17).

PMID: 36079065 PMC: 9456673. DOI: 10.3390/jcm11175136.

A hybrid 2D/4D-MRI methodology using simultaneous multislice imaging for radiotherapy guidance.

Keijnemans K, Borman P, Uijtewaal P, Woodhead P, Raaymakers B, Fast M Med Phys. 2022; 49(9):6068-6081.

PMID: 35694905 PMC: 9545880. DOI: 10.1002/mp.15802.

References

Tryggestad E, Flammang A, Hales R, Herman J, Lee J, McNutt T . 4D tumor centroid tracking using orthogonal 2D dynamic MRI: implications for radiotherapy planning. Med Phys. 2013; 40(9):091712. DOI: 10.1118/1.4818656. View

Park J, Park S, Kim H, Wu H, Carlson J, Kim J . A comparative planning study for lung SABR between tri-Co-60 magnetic resonance image guided radiation therapy system and volumetric modulated arc therapy. Radiother Oncol. 2016; 120(2):279-85. DOI: 10.1016/j.radonc.2016.06.013. View

Rueckert D, Sonoda L, Hayes C, Hill D, Leach M, Hawkes D . Nonrigid registration using free-form deformations: application to breast MR images. IEEE Trans Med Imaging. 1999; 18(8):712-21. DOI: 10.1109/42.796284. View

Caillet V, Keall P, Colvill E, Hardcastle N, OBrien R, Szymura K . MLC tracking for lung SABR reduces planning target volumes and dose to organs at risk. Radiother Oncol. 2017; 124(1):18-24. DOI: 10.1016/j.radonc.2017.06.016. View

Colvill E, Booth J, Nill S, Fast M, Bedford J, Oelfke U . A dosimetric comparison of real-time adaptive and non-adaptive radiotherapy: A multi-institutional study encompassing robotic, gimbaled, multileaf collimator and couch tracking. Radiother Oncol. 2016; 119(1):159-65. PMC: 4854175. DOI: 10.1016/j.radonc.2016.03.006. View

Lagendijk J, Raaymakers B, Raaijmakers A, Overweg J, Brown K, Kerkhof E . MRI/linac integration. Radiother Oncol. 2007; 86(1):25-9. DOI: 10.1016/j.radonc.2007.10.034. View

Lee D, Greer P, Ludbrook J, Arm J, Hunter P, Pollock S . Audiovisual Biofeedback Improves Cine-Magnetic Resonance Imaging Measured Lung Tumor Motion Consistency. Int J Radiat Oncol Biol Phys. 2016; 94(3):628-36. DOI: 10.1016/j.ijrobp.2015.11.017. View

Donnelly E, Parikh P, Lu W, Zhao T, Lechleiter K, Nystrom M . Assessment of intrafraction mediastinal and hilar lymph node movement and comparison to lung tumor motion using four-dimensional CT. Int J Radiat Oncol Biol Phys. 2007; 69(2):580-8. PMC: 2149909. DOI: 10.1016/j.ijrobp.2007.05.083. View

Mutic S, Dempsey J . The ViewRay system: magnetic resonance-guided and controlled radiotherapy. Semin Radiat Oncol. 2014; 24(3):196-9. DOI: 10.1016/j.semradonc.2014.02.008. View

10.

Machtay M, Paulus R, Moughan J, Komaki R, Bradley J, Choy H . Defining local-regional control and its importance in locally advanced non-small cell lung carcinoma. J Thorac Oncol. 2012; 7(4):716-22. PMC: 3335930. DOI: 10.1097/JTO.0b013e3182429682. View

11.

Paganelli C, Lee D, Greer P, Baroni G, Riboldi M, Keall P . Quantification of lung tumor rotation with automated landmark extraction using orthogonal cine MRI images. Phys Med Biol. 2015; 60(18):7165-78. DOI: 10.1088/0031-9155/60/18/7165. View

12.

Fallone B, Murray B, Rathee S, Stanescu T, Steciw S, Vidakovic S . First MR images obtained during megavoltage photon irradiation from a prototype integrated linac-MR system. Med Phys. 2009; 36(6):2084-8. DOI: 10.1118/1.3125662. View

13.

Liu H, Koch N, Starkschall G, Jacobson M, Forster K, Liao Z . Evaluation of internal lung motion for respiratory-gated radiotherapy using MRI: Part II-margin reduction of internal target volume. Int J Radiat Oncol Biol Phys. 2004; 60(5):1473-83. DOI: 10.1016/j.ijrobp.2004.05.054. View

14.

Modat M, Ridgway G, Taylor Z, Lehmann M, Barnes J, Hawkes D . Fast free-form deformation using graphics processing units. Comput Methods Programs Biomed. 2009; 98(3):278-84. DOI: 10.1016/j.cmpb.2009.09.002. View

15.

Seregni M, Paganelli C, Lee D, Greer P, Baroni G, Keall P . Motion prediction in MRI-guided radiotherapy based on interleaved orthogonal cine-MRI. Phys Med Biol. 2016; 61(2):872-87. DOI: 10.1088/0031-9155/61/2/872. View

16.

Wisotzky E, Fast M, Oelfke U, Nill S . Automated marker tracking using noisy X-ray images degraded by the treatment beam. Z Med Phys. 2014; 25(2):123-34. DOI: 10.1016/j.zemedi.2014.08.006. View

17.

Menten M, Fast M, Nill S, Kamerling C, McDonald F, Oelfke U . Lung stereotactic body radiotherapy with an MR-linac - Quantifying the impact of the magnetic field and real-time tumor tracking. Radiother Oncol. 2016; 119(3):461-6. PMC: 4936791. DOI: 10.1016/j.radonc.2016.04.019. View

18.

Plathow C, Klopp M, Fink C, Sandner A, Hof H, Puderbach M . Quantitative analysis of lung and tumour mobility: comparison of two time-resolved MRI sequences. Br J Radiol. 2005; 78(933):836-40. DOI: 10.1259/bjr/29483804. View

19.

Menten M, Wetscherek A, Fast M . MRI-guided lung SBRT: Present and future developments. Phys Med. 2017; 44:139-149. DOI: 10.1016/j.ejmp.2017.02.003. View

20.

Mazur T, Fischer-Valuck B, Wang Y, Yang D, Mutic S, Li H . SIFT-based dense pixel tracking on 0.35 T cine-MR images acquired during image-guided radiation therapy with application to gating optimization. Med Phys. 2016; 43(1):279. DOI: 10.1118/1.4938096. View