Introducing VESPIR: a new open-source software to investigate CT ventilation imaging in lung cancer radiotherapy
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VESPIR is an open-source toolkit for analyzing computed tomography ventilation imaging (CTVI) from 4DCT scans. It performs deformable image registration on inhale and exhale phases to quantify lung volume and density changes, generating CT-derived ventilation maps. Studies using VESPIR have found voxel-wise correlations as high as 0.80 between CTVI and nuclear medicine ventilation imaging like Gallium-68 PET scans. VESPIR validates CTVI across multiple sites and imaging modalities. It requires only a Windows laptop with MATLAB and the free Plastimatch deformable registration software. Researchers can contact the authors to obtain VESPIR and explore CTVI at their own clinics.
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Introducing VESPIR: a new open-source software to investigate CT ventilation imaging in lung cancer radiotherapy
- 2. SYDNEY MEDICAL SCHOOL J. Kipritidis, H. C. Woodruff & P. J. Keall Radiation Physics Laboratory UNIVERSITY OF SYDNEY Introducing VESPIR A new open-source effort to investigate CTVI in lung cancer radiotherapy Innovations in Cancer Treatment and Care Conference October 15th 2015
- 3. › Radiation pneumonitis is a major dose-limiting toxicity for lung cancer radiotherapy, symptomatic in up to 30% of patients* and fatal in up to 2%. D.A. Palma et al. 2013. IJROBP 85 pp. 444-50 3 What is the clinical driver for CT ventilation imaging (CTVI)? Galligas PET › New clinical trials are testing whether functionally-adaptive treatments can improve outcomes by sparing ventilated / perfused lung. D. A. Hoover et al. 2014. BMC Cancer 14:934 Technegas SPECT › Unfortunately, “gold standard” ventilation imaging is only performed for a few % of patients.
- 4. › CTVI visualizes air volume changes in 4DCT by quantifying breathing-induced lung motion using deformable image registration (DIR). T. Guerrero et al. 2006. PMB 51 pp. 777-791 4 high low Ventilation Compared to nuclear medicine imaging: 4DCT has high accessibility No added scan time/dose for lung cancer patients x No freeware tools for CTVI; difficult to implement from scratch! a. Import 4DCT b. Perform DIR c. Quantify volume or density changes What is the clinical driver for CT ventilation imaging (CTVI)? Data from Nepean Hospital (Penrith, NSW Australia)
- 5. › Ventilation via Scripted Pulmonary Image Registration (VESPIR) 5 a. vp = VESPIR_2(); VESPIR: The first open-source toolkit for CTVI b. vp.convertDCMAll(); c. vp.loadVolumesAll(); d. vp.segmentLungs(); f. vp.performDIR(); g. vp.Jdet2Vmap(); h. vp.Vmap2Dicom(); e. vp.getLungVolumes();
- 6. › We can evaluate the inhale exhale DIR in a freeware viewer (e.g. 3D Slicer): 6 Before registration (Anatomic mismatch!) After registration (Good match in lungs) VESPIR: The first open-source toolkit for CTVI
- 7. › We can compare CTVI’s based on different published analysis methods: 7 Lung volume change (“Jacobian-based”) Lung density change (“HU-based”) VESPIR: The first open-source toolkit for CTVI
- 8. › And understand the impact of different computational parameters Similarity metric? Similarity metric? DIR engine?DIR engine? B-spline grid spacing? B-spline grid spacing? DIR regularization? DIR regularization? Gaussian filtering? Gaussian filtering? Apply DIR lung mask? Apply DIR lung mask? Apply temporal filtering to 4D motion? Apply temporal filtering to 4D motion? λ = 0.001 λ = 0.1 λ = 1 λ = 5 λ = 10 high low 4D-CBCT J. Kipritidis et al. 2015. Med Phys 42 (3) pp. 1255-67 VESPIR enables cross-modality validation of CTVI across different clinical settings. VESPIR: The first open-source toolkit for CTVI Ventilation
- 9. Import 68 Ga 4D-PET/CTImport 68 Ga 4D-PET/CT Compute CTVICompute CTVI For each of 25 patients imaged at up to three timepoints: VESPIR “Ground truth” 3D Galligas PET3D Galligas PET HYPOTHESIS: CTVI should compare well against Galligas PET in terms of voxel- wise Spearman correlations. HYPOTHESIS: CTVI should compare well against Galligas PET in terms of voxel- wise Spearman correlations. High Low Ventilation Post-processing 1.Smoothing 2.Normalization Post-processing 1.Smoothing 2.Normalization
- 10. Emphysema (Bullae) Tumor obstruction Clipped artery Galligas PET Quantitative (voxel-wise correlation): r = 0.50 ± 0.17 Range: (0.11 – 0.80) Galligas PET CTVI CTVI 30 20 10 0 # Lung voxels Using VESPIR to validate CTVI Qualitative (visual comparison): › VESPIR has produced the highest voxel-wise correlations with nuclear medicine so far.
- 11. Quantitative (lobar-based correlation): Using VESPIR to validate CTVI Qualitative (visual comparison): › VESPIR has also been used to compare CTVI and 68 Ga-PET for surgical applications r = 0.96 (p<0.01) (11 patients, ~50 lobes) E. Eslick et al. Eur. J. of Cardio-Thorac. (2015)
- 12. Modalities 4D-CT 4D-CBCT 99m Tc SPECT 68 Ga PET 4D-CT VCU PMCC VCU NCCC PMCC RNSH BH-CT RNSH RNSH 4D-CBCT VCU NCCC • NCCC = Nepean Cancer Care Centre (Prospective) • RNSH = Royal North Shore Hospital (Prospective) • PMCC = Peter MacCallum Cancer Centre (Retrospective) • VCU = Virginia Commonwealth University (Retrospective) We are using VESPIR to validate CTVI across multiple modalities: LEGEND Published Under-way Where is VESPIR being used?
- 13. › You can explore CT ventilation imaging at your clinic! All you need is: - All you need is a Windows laptop running MATLAB 2014 or newer* - An installation of Plastimatch, the freeware DIR software from: http://plastimatch.org › To obtain a copy of VESPIR, send me an email (or say hello!) john.kipritidis@sydney.edu.au › You can find out more about CT ventilation imaging here: http://sydney.edu.au/medicine/radiation-physics/research-projects/CT-ventilation-imaging.php 13 What do I need to run VESPIR? (and how can I get it?) *A standalone is version coming soon!
- 14. Acknowledgements Disclosure This work was supported by a Cancer Institute NSW Early Career Fellowship, Cancer Australia Priority-driven Collaborative Cancer Research Grant APP1060919 and an NHMRC Australia Fellowship.
Notes de l'éditeur
- To understand why ventilation imaging is important in lung cancer treatment, consider that radiation pneumonitis remains a major dose-limiting toxicity for lung cancer radiation therapy. Pneumonitis can involve pulmonary function loss that is symptomatic in up to 30% of patients, and fatal in up to 2% New clinical trials are testing whether functionally-guided treatments can improve outcomes by minimizing irradiation of healthy lung, that is, lung that is ventilated or perfused. This necessitates functional lung imaging; unfortunately the clinical Gold standard nuclear medicine methods, such as SPECT and PET, are only performed for a small %-age of lung cancer patients as part of clinical trials.
- An exciting new alternative, CT ventilation imaging, or CTVI, has been proposed to extract lung ventilation from 4DCT scans. This technique aims to visualize air volume changes in the lung by estimating breathing-induced changes in lung density or volume using deformable image registration (or DIR). The main appeal of CTVI is that it requires only image processing of 4DCT, which is already a standard imaging component of modern lung cancer radiation therapy. However a barrier to clincial implementation is that there are no freeware tools for CTVI; developing a workflow from scratch is a huge task.
- VESPIR provides a streamlined path to CT ventilation images (less than 10 minutes, only 8 commands needed!). Output is Dicom which can be directly input back into a treatment planning system.
- Practically, it’s rare that different CTVIs will agree so well! In fact CTVI is sensitive to many computational parameters. (I) What similarity metric should we use? (ii) How coarse or fine does the DIR result need to be? How many resolution stages? (iii) What level of spatial regularization of the motion fields is required? For example, enforcing different levels of motion-field regularization (here it’s the lambda value here) can lead to vastly different looking CTVIs. VESPIR is important to rapidly test different CTVI types versus “ground truth” ventilation imaging in different clinical situations.
- - Here’s one such validation study: we analyzed 62 Galligas PET ventilation scans for 25 lung cancer patients, imaged at up to three timepoints using a combined 4D-PET/CT scanner. - For each scan, we compared the output from VESPIR with the ground truth, 3D Galligas PET scan. We quantify the voxel-wise Spearman correlations, indicating the correspondence between CTVI and Galligas PET.
- - Qualitatively, we observe that the accuracy of CTVI can depend on the ventilation defects involved. Here we see coronal cross sections of Galligas PET for three different patients. One with an emphysematous bullae, another with tumor obstruction, one with a clipped artery which appears as a high-density region on CT, and another with relatively normal ventilation. The red arrows indicate the defect region of interest.
- So what are we doing to validate this new technology? We are correlating baseline CT-ventilation, either 4D-CT breath hold CT or 4D cone beam CT, to other modalities including Technegas ventilation SPECT, respiratory gated Galligas PET as well as pulmonary function tests. This is all patient imaging data, some resulting from QA studies collecting 4D imaging, others are prospective clinical trials. You may be wondering why, in some cases I’m comparing a modality against itself; this is referring to multiple timepoint data, and I’ll get onto that shortly.
- * Standalone version coming soon!
- Finally I’d like to thank all the researchers that made this work possible. Thank you.