Highlights
- •We propose a simplified algorithm, VIAAVG, which is independent on DIR and requires only AVG CT as input.
- •Accuracy and efficiency are evaluated for 50 patients, which is the largest cohort as far as we know.
- •VIAAVG shows nearly substantial similarity with gold standard, VISPECT, which is higher than other proposed algorithms.
- •VIAAVG takes much less time to compute CTVI than other algorithms proposed before.
- •VIAAVG is more convenient for clinical use, since structures, dose, lung function are all defined on the same AVG CT.
Abstract
Purpose
It is still not conclusive which four-dimensional computed tomography (4DCT)-based
ventilation imaging algorithm is most accurate and efficient. In this study, we proposed
a simplified algorithm (VIAAVG) which only requires the average computed tomography
(AVG CT) as input, and quantitatively compared its accuracy and efficiency with three
other popular algorithms.
Material and methods
Fifty patients with lung or esophageal cancer who underwent radiotherapy were enrolled.
Single photon emission computed tomography (SPECT) ventilation images (VI-SPECT) and
4DCT were acquired 1–3 days before the first treatment session. The end of exhalation
and the end of inhalation CT were registered to derive deformable vector field (DVF)
using MIMvista. 4DCT-based ventilation images (CTVI) were first calculated respectively
by means of four algorithms (VIAJAC, VIAHU, VIAPRO and VIAAVG). The computation times
were compared using paired t-test. The corresponding CTVIs (CTVIJAC, CTVIHU, CTVIPRO and CTVIAVG) and VI-SPECT
were segmented into three equal sub-volumes (high, medium and low function lung, respectively)
after smoothing and normalization. The Dice Similarity Coefficients (DSCs) were calculated
for each sub-volume between each CTVI and VI-SPECT. The average DSCs for high, medium
and low function lung in different CTVIs for each patient were compared using paired
t-test.
Results
The mean DSCs for CTVIJAC, CTVIHU, CTVIPRO and CTVIAVG were 0.3255, 0.4465, 0.5865
and 0.5958, respectively. The average computation times for CTVIJAC, CTVIHU, CTVIPRO
and CTVIAVG were 18.3 s, 24.2 s, 144.8 s and 15.0 s.
Conclusion
VIAAVG is available for clinical use because of its high accuracy, improved efficiency
and less input requirement compared to the other algorithms.
Keywords
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References
- SPECT V/Q in lung cancer radiotherapy planning.Semin Nucl Med. 2019; 49: 31-36
- Functional image-guided radiotherapy planning for normal lung avoidance.Clin Oncol (R Coll Radiol). 2016; 28: 695-707
- Investigation of four-dimensional computed tomography-based pulmonary ventilation imaging in patients with emphysematous lung regions.Phys Med Biol. 2011; 56: 2279-2298
- 4DCT-based measurement of changes in pulmonary function following a course of radiation therapy.Med Phys. 2010; 37: 1261-1272
- Normalization of ventilation data from 4D-CT to facilitate comparison between datasets acquired at different times.PLoS One. 2013; 8e84083
- Analysis of long-term 4-dimensional computed tomography regional ventilation after radiation therapy.Int J Radiat Oncol Biol Phys. 2015; 92: 683-690
- Measuring interfraction and intrafraction lung function changes during radiation therapy using four-dimensional cone beam CT ventilation imaging.Med Phys. 2015; 42: 1255-1267
- The first patient treatment of computed tomography ventilation functional image-guided radiotherapy for lung cancer.Radiother Oncol. 2016; 118: 227-231
- Combined ventilation and perfusion imaging correlates with the dosimetric parameters of radiation pneumonitis in radiation therapy planning for lung cancer.Int J Radiat Oncol Biol Phys. 2015; 93: 778-787
- Use of 4-dimensional computed tomography-based ventilation imaging to correlate lung dose and function with clinical outcomes.Int J Radiat Oncol Biol Phys. 2013; 86: 366-371
- Reduction of normal lung irradiation in locally advanced non-small-cell lung cancer patients, using ventilation images for functional avoidance.Int J Radiat Oncol Biol Phys. 2007; 68: 562-571
- Impact of four-dimensional computed tomography pulmonary ventilation imaging-based functional avoidance for lung cancer radiotherapy.Int J Radiat Oncol Biol Phys. 2011; 79: 279-288
- Functional image-guided radiotherapy planning in respiratory-gated intensity-modulated radiotherapy for lung cancer patients with chronic obstructive pulmonary disease.Int J Radiat Oncol Biol Phys. 2012; 82: e663-e670
- IMRT treatment plans and functional planning with functional lung imaging from 4D-CT for thoracic cancer patients.Radiat Oncol. 2013; 8: 3
- CT ventilation functional image-based IMRT treatment plans are comparable to SPECT ventilation functional image-based plans.Radiother Oncol. 2016; 118: 521-527
- Quantification of regional ventilation from treatment planning CT.Int J Radiat Oncol Biol Phys. 2005; 62: 630-634
- Registration-based estimates of local lung tissue expansion compared to xenon CT measures of specific ventilation.Med Image Anal. 2008; 12: 752-763
- Estimating lung ventilation directly from 4D CT Hounsfield unit values.Med Phys. 2016; 43: 33
- Technical and analytical advances in pulmonary ventilation SPECT with xenon-133 gas and Tc-99m-Technegas.Ann Nucl Med. 2002; 16: 303-310
- High-resolution imaging of pulmonary ventilation and perfusion with 68Ga-VQ respiratory gated (4-D) PET/CT.Eur J Nucl Med Mol Imaging. 2014; 41: 343-349
- Validating and improving CT ventilation imaging by correlating with ventilation 4D-PET/CT using 68Ga-labeled nanoparticles.Med Phys. 2014; 41011910
- Pulmonary ventilation imaging based on 4-dimensional computed tomography: comparison with pulmonary function tests and SPECT ventilation images.Int J Radiat Oncol Biol Phys. 2014; 90: 414-422
- Ventilation from four-dimensional computed tomography: density versus Jacobian methods.Phys Med Biol. 2010; 55: 4661-4685
- The VAMPIRE challenge: a multi-institutional validation study of CT ventilation imaging.Med Phys. 2019; 46: 1198-1217
- Ventilation measured on clinical 4D-CBCT: increased ventilation accuracy through improved image quality.Radiother Oncol. 2017; 125: 459-463
- Technical note: correction for the effect of breathing variations in CT pulmonary ventilation imaging.Med Phys. 2018; 45: 322-327
- A framework for evaluation of deformable image registration spatial accuracy using large landmark point sets.Phys Med Biol. 2009; 54: 1849-1870
- A voxel-by-voxel comparison of deformable vector fields obtained by three deformable image registration algorithms applied to 4DCT lung studies.Front Oncol. 2015; 5: 17
- 4D CT lung ventilation images are affected by the 4D CT sorting method.Med Phys. 2013; 40101907
- 4D-CT imaging of a volume influenced by respiratory motion on multi-slice CT.Med Phys. 2004; 31: 333-340
- Reproducibility of four-dimensional computed tomography-based lung ventilation imaging.Acad Radiol. 2012; 19: 1554-1565
- Dosimetric comparison of treatment plans based on free breathing, maximum, and average intensity projection CTs for lung cancer SBRT.Med Phys. 2012; 39: 2754-2760
- A 4D biomechanical lung phantom for joint segmentation/registration evaluation.Phys Med Biol. 2016; 61: 7012-7030
- The numerical stability of transformation-based CT ventilation.Int J Comput Assist Radiol Surg. 2017; 12: 569-580
Article info
Publication history
Published online: August 12, 2019
Accepted:
August 5,
2019
Received in revised form:
July 8,
2019
Received:
January 18,
2019
Identification
Copyright
© 2019 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
