Four-Dimensional Computed Tomography Ventilation Image-Guided Lung Functional Avoidance Radiation Therapy: A Single-Arm Prospective Pilot Clinical Trial.

PURPOSE: The primary objective of this prospective pilot trial was to assess the safety and feasibility of lung functional avoidance radiation therapy (RT) with 4-dimensional (4D) computed tomography (CT) ventilation imaging. METHODS AND MATERIALS: Patients with primary lung cancer or metastatic disease to the lungs to receive conventionally fractionated RT (CFRT) or stereotactic body RT (SBRT) were eligible. Standard-of-care 4D-CT scans were used to generate ventilation images through image processing/analysis. Each patient required a standard intensity modulated RT plan and ventilation image guided functional avoidance plan. The primary endpoint was the safety of functional avoidance RT, defined as the rate of grade ≥3 adverse events (AEs) that occurred ≤12 months after treatment. Protocol treatment was considered safe if the rates of grade ≥3 pneumonitis and esophagitis were <13% and <21%, respectively for CFRT, and if the rate of any grade ≥3 AEs was <28% for SBRT. Feasibility of functional avoidance RT was assessed by comparison of dose metrics between the 2 plans using the Wilcoxon signed-rank test. RESULTS: Between May 2015 and November 2019, 34 patients with non-small cell lung cancer were enrolled, and 33 patients were evaluable (n = 24 for CFRT; n = 9 for SBRT). Median follow-up was 14.7 months. For CFRT, the rates of grade ≥3 pneumonitis and esophagitis were 4.2% (95% confidence interval, 0.1%-21.1%) and 12.5% (2.7%-32.4%). For SBRT, no patients developed grade ≥3 AEs. Compared with the standard plans, the functional avoidance plans significantly (P < .01) reduced the lung dose-function metrics without compromising target coverage or adherence to standard organs at risk constraints. CONCLUSIONS: This study, representing one of the first prospective investigations on lung functional avoidance RT, demonstrated that the 4D-CT ventilation image guided functional avoidance RT that significantly reduced dose to ventilated lung regions could be safely administered, adding to the growing body of evidence for its clinical utility.

Changes in Regional Ventilation During Treatment and Dosimetric Advantages of CT Ventilation Image Guided Radiation Therapy for Locally Advanced Lung Cancer.

PURPOSE: Lung functional image guided radiation therapy (RT) that avoids irradiating highly functional regions has potential to reduce pulmonary toxicity following RT. Tumor regression during RT is common, leading to recovery of lung function. We hypothesized that computed tomography (CT) ventilation image-guided treatment planning reduces the functional lung dose compared to standard anatomic image-guided planning in 2 different scenarios with or without plan adaptation. METHODS AND MATERIALS: CT scans were acquired before RT and during RT at 2 time points (16-20 Gy and 30-34 Gy) for 14 patients with locally advanced lung cancer. Ventilation images were calculated by deformable image registration of four-dimensional CT image data sets and image analysis. We created 4 treatment plans at each time point for each patient: functional adapted, anatomic adapted, functional unadapted, and anatomic unadapted plans. Adaptation was performed at 2 time points. Deformable image registration was used for accumulating dose and calculating a composite of dose-weighted ventilation used to quantify the lung accumulated dose-function metrics. The functional plans were compared with the anatomic plans for each scenario separately to investigate the hypothesis at a significance level of 0.05. RESULTS: Tumor volume was significantly reduced by 20% after 16 to 20 Gy (P = .02) and by 32% after 30 to 34 Gy (P < .01) on average. In both scenarios, the lung accumulated dose-function metrics were significantly lower in the functional plans than in the anatomic plans without compromising target volume coverage and adherence to constraints to critical structures. For example, functional planning significantly reduced the functional mean lung dose by 5.0% (P < .01) compared to anatomic planning in the adapted scenario and by 3.6% (P = .03) in the unadapted scenario. CONCLUSIONS: This study demonstrated significant reductions in the accumulated dose to the functional lung with CT ventilation image-guided planning compared to anatomic image-guided planning for patients showing tumor regression and changes in regional ventilation during RT.

Cardiac magnetic resonance T1 and extracellular volume mapping with motion correction and co-registration based on fast elastic image registration.

OBJECTIVE: Our aim was to investigate the technical feasibility of a novel motion compensation method for cardiac magntic resonance (MR) T1 and extracellular volume fraction (ECV) mapping. MATERIALS AND METHODS: Native and post-contrast T1 maps were obtained using modified look-locker inversion recovery (MOLLI) pulse sequences with acquisition scheme defined in seconds. A nonrigid, nonparametric, fast elastic registration method was applied to generate motion-corrected T1 maps and subsequently ECV maps. Qualitative rating was performed based on T1 fitting-error maps and overlay images. Local deformation vector fields were produced for quantitative assessment. Intra- and inter-observer reproducibility were compared with and without motion compensation. RESULTS: Eighty-two T1 and 39 ECV maps were obtained in 21 patients with diverse myocardial diseases. Approximately 60% demonstrated clear quality improvement after motion correction for T1 mapping, particularly for the poor-rating cases (23% before vs 2% after). Approximately 67% showed further improvement with co-registration in ECV mapping. Although T1 and ECV values were not clinically significantly different before and after motion compensation, there was improved intra- and inter-observer reproducibility after motion compensation. CONCLUSIONS: Automated motion correction and co-registration improved the qualitative assessment and reproducibility of cardiac MR T1 and ECV measurements, allowing for more reliable ECV mapping.

Technical Note: Correction for the effect of breathing variations in CT pulmonary ventilation imaging.

PURPOSE: The accuracy and precision of computed tomography (CT) pulmonary ventilation imaging with conventional CT scanners are limited by breathing variations. We propose a method to correct for the effect of breathing variations in CT ventilation imaging based on external respiratory signals acquired throughout a scan. METHODS: The proposed method is based on: (a) calculating voxel-by-voxel abdominal surface motion ranges using four-dimensional (4D) CT image datasets spatiotemporally correlated with external respiratory monitor data, and (b) applying the correction factor, which is defined as the ratio of the overall mean of the abdominal surface motion range in the lungs to that of each voxel, to the CT ventilation value. The performance of the proposed method was investigated by comparing voxel-wise correlations of the uncorrected and corrected CT ventilation images with single-photon emission CT (SPECT) ventilation images as a ground truth for nine patients. CT ventilation images were calculated by deformable image registration of the 4D-CT image datasets, followed by calculation of regional volume changes. A Steiger's Z-test was used to determine the statistical significance of the difference between the correlations for the uncorrected and corrected CT ventilation images. RESULTS: The proposed correction method resulted in significant increases (P < 0.05) in the correlation between CT and SPECT ventilation in three patients, trends toward significant increase (P: 0.13-0.18) in two patients, no significant differences in three patients, and a significantly decreased correlation in one patient. The average standard deviation of the abdominal surface motion range in three patients showing significant increases was 0.27 (range 0.10-0.37), which was greater than 0.17 (range 0.07-0.38) in the other six patients. CONCLUSIONS: The proposed method to correct for the effect of breathing variations could be readily implemented and has the potential to improve the accuracy of CT ventilation imaging as demonstrated in a nine-patient study.

Which Criteria Applied in Multi-Phasic CT Can Predict Early Tumor Response in Patients with Hepatocellular Carcinoma Treated Using Conventional TACE: RECIST, mRECIST, EASL or qEASL?

PURPOSE: Our study aimed to evaluate quantitative tumor response assessment (quantitative EASL-[qEASL]) on computed tomography (CT) images in patients with hepatocellular carcinoma (HCC) treated using conventional transarterial chemoembolization (cTACE), compared to existing 1-dimensional and 2-dimensional methods (RECIST, mRECIST, EASL). MATERIALS AND METHODS: In this IRB-approved, single-institution retrospective cohort study, 52 consecutive patients with intermediate-stage HCC were consecutively included. All patients underwent contrast-enhanced CT scan at baseline and 4 weeks after cTACE. RESULTS: Median follow-up period was 13.5 months (range 1.2-54.1). RECIST, mRECIST and EASL identified progression in 2 (4%), 1 (2%) and 1 (2%) patients, respectively, whereas qEASL identified 10 (19%) patients. qEASL was the only tumor response method able to predict survival among different tumor response groups (P < 0.05), whereas RECIST, mRECIST and EASL did not (P > 0.05). Both EASL and qEASL were able to identify responders and non-responders and were predictive of survival (P < 0.05). Multivariate analysis showed that progression was an independent predictor of overall survival with hazard ratio of 1.9 (P = 0.025). Patients who demonstrated progression with qEASL had significantly shorter survival than those with non-progression (7.6 vs. 20.4 months, P = 0.012). Similar multivariate analysis using RECIST, mRECIST and EASL could not be performed because too few patients were categorized as progressive disease. CONCLUSION: qEASL could be applied on CT images to assess tumor response following cTACE and is a more sensitive biomarker to predict survival and identify tumor progression than RECIST, mRECIST and EASL at an early time point. LEVEL OF EVIDENCE: Level 2a, retrospective cohort study.

CT ventilation functional image-based IMRT treatment plans are comparable to SPECT ventilation functional image-based plans.

PURPOSE: To investigate the hypothesis that CT ventilation functional image-based IMRT plans designed to avoid irradiating highly-functional lung regions are comparable to single-photon emission CT (SPECT) ventilation functional image-based plans. METHODS AND MATERIALS: Three IMRT plans were created for eight thoracic cancer patients using: (1) CT ventilation functional images, (2) SPECT ventilation functional images, and (3) anatomic images (no functional images). CT ventilation images were created by deformable image registration of 4D-CT image data sets and quantitative analysis. The resulting plans were analyzed for the relationship between the deviations of CT-functional plan metrics from anatomic plan metrics (ΔCT-anatomic) and those of SPECT-functional plans (ΔSPECT-anatomic), and moreover for agreements of various metrics between the CT-functional and SPECT-functional plans. RESULTS: The relationship between ΔCT-anatomic and ΔSPECT-anatomic was strong (e.g., R=0.94; linear regression slope 0.71). The average differences and 95% limits of agreement between the CT-functional and SPECT-functional plan metrics (except for monitor units) for various structures were mostly less than 1% and 2%, respectively. CONCLUSIONS: This study demonstrated a reasonable agreement between the CT ventilation functional image-based IMRT plans and SPECT-functional plans, suggesting the potential for CT ventilation imaging to serve as a surrogate for SPECT ventilation in functional image-guided radiotherapy.

The first patient treatment of computed tomography ventilation functional image-guided radiotherapy for lung cancer.

BACKGROUND AND PURPOSE: Radiotherapy that selectively avoids irradiating highly-functional lung regions may reduce pulmonary toxicity. We report on the first clinical implementation and patient treatment of lung functional image-guided radiotherapy using an emerging technology, computed tomography (CT) ventilation imaging. MATERIAL AND METHODS: A protocol was developed to investigate the safety and feasibility of CT ventilation functional image-guided radiotherapy. CT ventilation imaging is based on (1) deformable image registration of four-dimensional (4D) CT images, and (2) quantitative image analysis for regional volume change, a surrogate for ventilation. CT ventilation functional image-guided radiotherapy plans were designed to minimize specific lung dose-function metrics, including functional V20 (fV20), while maintaining target coverage and meeting standard constraints to other critical organs. RESULTS: CT ventilation functional image-guided treatment planning reduced the lung fV20 by 5% compared to an anatomic image-guided plan for an enrolled patient with stage IIIB non-small cell lung cancer. Although the doses to several other critical organs increased, the necessary constraints were all met. CONCLUSIONS: An emerging technology, CT ventilation imaging has been translated into the clinic and used in functional image-guided radiotherapy for the first time. This milestone represents an important first step toward hypothetically reduced pulmonary toxicity in lung cancer radiotherapy.

Symmetric Biomechanically Guided Prone-to-Supine Breast Image Registration.

Prone-to-supine breast image registration has potential application in the fields of surgical and radiotherapy planning, image guided interventions, and multi-modal cancer diagnosis, staging, and therapy response prediction. However, breast image registration of three dimensional images acquired in different patient positions is a challenging problem, due to large deformations induced to the soft breast tissue caused by the change in gravity loading. We present a symmetric, biomechanical simulation based registration framework which aligns the images in a central, virtually unloaded configuration. The breast tissue is modelled as a neo-Hookean material and gravity is considered as the main source of deformation in the original images. In addition to gravity, our framework successively applies image derived forces directly into the unloading simulation in place of a subsequent image registration step. This results in a biomechanically constrained deformation. Using a finite difference scheme avoids an explicit meshing step and enables simulations to be performed directly in the image space. The explicit time integration scheme allows the motion at the interface between chest and breast to be constrained along the chest wall. The feasibility and accuracy of the approach presented here was assessed by measuring the target registration error (TRE) using a numerical phantom with known ground truth deformations, nine clinical prone MRI and supine CT image pairs, one clinical prone-supine CT image pair and four prone-supine MRI image pairs. The registration reduced the mean TRE for the numerical phantom experiment from initially 19.3 to 0.9 mm and the combined mean TRE for all fourteen clinical data sets from 69.7 to 5.6 mm.

Crystal structure of tris-(N-methyl-salicylaldiminato-κ(2) N,O)vanadium(III).

The structure of the title complex, [V(C8H8NO)3], comprises neutral and discrete complexes, in which the V(III) cation is coordinated by three anionic N-methyl-alicylaldiminate ligands within a slightly distorted mer-N3O3 octa-hedral geometry. In the crystal structure, the mol-ecules are linked via C-H⋯O hydrogen bonds into supra-molecular chains that extend along the c axis.

Crystal structure of tris-(N-methyl-salicyl-aldiminato-κ(2) N,O)chromium(III).

The crystal structure of the title compound, [Cr(C8H8NO)3], is isotypic with the vanadium(III) analogue. The asymmetric unit consists of one Cr(3+) cation and three N-methyl-salicylaldiminate anions. The metal cation is octa-hedrally coordinated by three N,O-chelating N-methyl-salicylaldiminate ligands, leading to discrete and neutral complexes. In the crystal, neighbouring complexes are linked via C-H⋯O hydrogen-bonding inter-actions into chains propagating parallel to the c axis.

Pulmonary ventilation imaging based on 4-dimensional computed tomography: comparison with pulmonary function tests and SPECT ventilation images.

PURPOSE: 4-dimensional computed tomography (4D-CT)-based pulmonary ventilation imaging is an emerging functional imaging modality. The purpose of this study was to investigate the physiological significance of 4D-CT ventilation imaging by comparison with pulmonary function test (PFT) measurements and single-photon emission CT (SPECT) ventilation images, which are the clinical references for global and regional lung function, respectively. METHODS AND MATERIALS: In an institutional review board-approved prospective clinical trial, 4D-CT imaging and PFT and/or SPECT ventilation imaging were performed in thoracic cancer patients. Regional ventilation (V4DCT) was calculated by deformable image registration of 4D-CT images and quantitative analysis for regional volume change. V4DCT defect parameters were compared with the PFT measurements (forced expiratory volume in 1 second (FEV1; % predicted) and FEV1/forced vital capacity (FVC; %). V4DCT was also compared with SPECT ventilation (VSPECT) to (1) test whether V4DCT in VSPECT defect regions is significantly lower than in nondefect regions by using the 2-tailed t test; (2) to quantify the spatial overlap between V4DCT and VSPECT defect regions with Dice similarity coefficient (DSC); and (3) to test ventral-to-dorsal gradients by using the 2-tailed t test. RESULTS: Of 21 patients enrolled in the study, 18 patients for whom 4D-CT and either PFT or SPECT were acquired were included in the analysis. V4DCT defect parameters were found to have significant, moderate correlations with PFT measurements. For example, V4DCT(HU) defect volume increased significantly with decreasing FEV1/FVC (R=-0.65, P<.01). V4DCT in VSPECT defect regions was significantly lower than in nondefect regions (mean V4DCT(HU) 0.049 vs 0.076, P<.01). The average DSCs for the spatial overlap with SPECT ventilation defect regions were only moderate (V4DCT(HU)0.39 ± 0.11). Furthermore, ventral-to-dorsal gradients of V4DCT were strong (V4DCT(HU) R(2) = 0.69, P=.08), which was similar to VSPECT (R(2) = 0.96, P<.01). CONCLUSIONS: An 18-patient study demonstrated significant correlations between 4D-CT ventilation and PFT measurements as well as SPECT ventilation, providing evidence toward the validation of 4D-CT ventilation imaging.

Dynamic CT perfusion imaging of the myocardium: a technical note on improvement of image quality.

OBJECTIVE: To improve image and diagnostic quality in dynamic CT myocardial perfusion imaging (MPI) by using motion compensation and a spatio-temporal filter. METHODS: Dynamic CT MPI was performed using a 256-slice multidetector computed tomography scanner (MDCT). Data from two different patients-with and without myocardial perfusion defects-were evaluated to illustrate potential improvements for MPI (institutional review board approved). Three datasets for each patient were generated: (i) original data (ii) motion compensated data and (iii) motion compensated data with spatio-temporal filtering performed. In addition to the visual assessment of the tomographic slices, noise and contrast-to-noise-ratio (CNR) were measured for all data. Perfusion analysis was performed using time-density curves with regions-of-interest (ROI) placed in normal and hypoperfused myocardium. Precision in definition of normal and hypoperfused areas was determined in corresponding coloured perfusion maps. RESULTS: The use of motion compensation followed by spatio-temporal filtering resulted in better alignment of the cardiac volumes over time leading to a more consistent perfusion quantification and improved detection of the extend of perfusion defects. Additionally image noise was reduced by 78.5%, with CNR improvements by a factor of 4.7. The average effective radiation dose estimate was 7.1±1.1 mSv. CONCLUSION: The use of motion compensation and spatio-temporal smoothing will result in improved quantification of dynamic CT MPI using a latest generation CT scanner.

4D CT lung ventilation images are affected by the 4D CT sorting method.

PURPOSE: Four-dimensional (4D) computed tomography (CT) ventilation imaging is a novel promising technique for lung functional imaging. The current standard 4D CT technique using phase-based sorting frequently results in artifacts, which may deteriorate the accuracy of ventilation imaging. The purpose of this study was to quantify the variability of 4D CT ventilation imaging due to 4D CT sorting. METHODS: 4D CT image sets from nine lung cancer patients were each sorted by the phase-based method and anatomic similarity-based method, designed to reduce artifacts, with corresponding ventilation images created for each method. Artifacts in the resulting 4D CT images were quantified with the artifact score which was defined based on the difference between the normalized cross correlation for CT slices within a CT data segment and that for CT slices bordering the interface between adjacent CT data segments. The ventilation variation was quantified using voxel-based Spearman rank correlation coefficients for all lung voxels, and Dice similarity coefficients (DSC) for the spatial overlap of low-functional lung volumes. Furthermore, the correlations with matching single-photon emission CT (SPECT) ventilation images (assumed ground truth) were evaluated for three patients to investigate which sorting method provides higher physiologic accuracy. RESULTS: Anatomic similarity-based sorting reduced 4D CT artifacts compared to phase-based sorting (artifact score, 0.45 ± 0.14 vs 0.58 ± 0.24, p = 0.10 at peak-exhale; 0.63 ± 0.19 vs 0.71 ± 0.31, p = 0.25 at peak-inhale). The voxel-based correlation between the two ventilation images was 0.69 ± 0.26 on average, ranging from 0.03 to 0.85. The DSC was 0.71 ± 0.13 on average. Anatomic similarity-based sorting yielded significantly fewer lung voxels with paradoxical negative ventilation values than phase-based sorting (5.0 ± 2.6% vs 9.7 ± 8.4%, p = 0.05), and improved the correlation with SPECT ventilation regionally. CONCLUSIONS: The variability of 4D CT ventilation imaging due to 4D CT sorting was moderate overall and substantial in some cases, suggesting that 4D CT artifacts are an important source of variations in 4D CT ventilation imaging. Reduction of 4D CT artifacts provided more physiologically convincing and accurate ventilation estimates. Further studies are needed to confirm this result.

Reproducibility of four-dimensional computed tomography-based lung ventilation imaging.

RATIONALE AND OBJECTIVES: A novel ventilation imaging method based on four-dimensional (4D) computed tomography (CT) has been applied to the field of radiation oncology. Understanding its reproducibility is a prerequisite for clinical applications. The purpose of this study was to quantify the reproducibility of 4D CT ventilation imaging over different days and the same session. MATERIALS AND METHODS: Two ventilation images were created from repeat 4D CT scans acquired over the average time frames of 15 days for 6 lung cancer patients and 5 minutes for another 6 patients. The reproducibility was quantified using the voxel-based Spearman rank correlation coefficients for all lung voxels and Dice similarity coefficients (DSC) for the spatial overlap of segmented high-, moderate-, and low-functional lung volumes. Furthermore, the relationship between the variation in abdominal motion range as a measure of the depth of breathing and variation in ventilation was evaluated using linear regression. RESULTS: The voxel-based correlation between the two ventilation images was moderate on average (0.50 ± 0.15). The DSCs were also moderate for the high- (0.60 ± 0.08), moderate- (0.46 ± 0.06), and low-functional lung (0.58 ± 0.09). No patients demonstrated strong correlations. The relationship between the motion range variation and ventilation variation was found to be moderate and significant. CONCLUSIONS: We investigated the reproducibility of 4D CT ventilation imaging over the time frames of 15 days and 5 minutes and found that it was only moderately reproducible. Respiratory variation during 4D CT scans was found to deteriorate the reproducibility. Improvement of 4D CT imaging is necessary to increase the reproducibility of 4D CT ventilation imaging.

Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge.

EMPIRE10 (Evaluation of Methods for Pulmonary Image REgistration 2010) is a public platform for fair and meaningful comparison of registration algorithms which are applied to a database of intrapatient thoracic CT image pairs. Evaluation of nonrigid registration techniques is a nontrivial task. This is compounded by the fact that researchers typically test only on their own data, which varies widely. For this reason, reliable assessment and comparison of different registration algorithms has been virtually impossible in the past. In this work we present the results of the launch phase of EMPIRE10, which comprised the comprehensive evaluation and comparison of 20 individual algorithms from leading academic and industrial research groups. All algorithms are applied to the same set of 30 thoracic CT pairs. Algorithm settings and parameters are chosen by researchers expert in the configuration of their own method and the evaluation is independent, using the same criteria for all participants. All results are published on the EMPIRE10 website (http://empire10.isi.uu.nl). The challenge remains ongoing and open to new participants. Full results from 24 algorithms have been published at the time of writing. This paper details the organization of the challenge, the data and evaluation methods and the outcome of the initial launch with 20 algorithms. The gain in knowledge and future work are discussed.

Four-dimensional computed tomography pulmonary ventilation images vary with deformable image registration algorithms and metrics.

PURPOSE: A novel pulmonary ventilation imaging technique based on four-dimensional (4D) CT has advantages over existing techniques and could be used for functional avoidance in radiotherapy. There are various deformable image registration (DIR) algorithms and two classes of ventilation metric that can be used for 4D-CT ventilation imaging, each yielding different images. The purpose of this study was to quantify the variability of the 4D-CT ventilation to DIR algorithms and metrics. METHODS: 4D-CT ventilation images were created for 12 patients using different combinations of two DIR algorithms, volumetric (DIR(vol)) and surface-based (DIR(sur)), yielding two displacement vector fields (DVFs) per patient (DVF(voI) and DVF(sur)), and two metrics, Hounsfield unit (HU) change (V(HU)) and Jacobian determinant of deformation (V(Jac)), yielding four ventilation image sets (V(HU)(vol), V(HU)(sur), V(Jac)(voI), and V(Jac)(sur). First DVF(vol) and DVF(sur) were compared visually and quantitatively to the length of 3D displacement vector difference. Second, four ventilation images were compared based on voxel-based Spearman's rank correlation coefficients and coefficients of variation as a measure of spatial heterogeneity. V(HU)(vol) was chosen as the reference for the comparison. RESULTS: The mean length of 3D vector difference between DVF(vol) and DVF(sur) was 2.0 +/- 1.1 mm on average, which was smaller than the voxel dimension of the image set and the variations. Visually, the reference V(HU)(vol) demonstrated similar regional distributions with V(HU)(sur); the reference, however, was markedly different from V(Jac)(vol) and V((Jac)(sur). The correlation coefficients of V(HU)(vol) with V(HU)(sur), V(Jac)(vol) and V(Jac)(sur) were 0.77 +/- 0.06, 0.25 +/- 0.06 and 0.15 +/- 0.07, respectively, indicating that the metric introduced larger variations in the ventilation images than the DIR algorithm. The spatial heterogeneities for V(HU)(vol), 'V(HU)(sur), V(Jac)(vol), and V(Jac)(sur) were 1.8 +/- 1.6, 1.8 +/- 1.5 (p = 0. 85), 0.6 +/- 0.2 (p = 0.02), and 0.7 +/- 0.2 (p = 0.03), respectively, also demonstrating that the metric introduced larger variations. CONCLUSIONS: 4D-CT pulmonary ventilation images vary widely with DIR algorithms and metrics. Careful physiologic validation to determine the appropriate DIR algorithm and metric is needed prior to its applications.

Investigation of four-dimensional computed tomography-based pulmonary ventilation imaging in patients with emphysematous lung regions.

A pulmonary ventilation imaging technique based on four-dimensional (4D) computed tomography (CT) has advantages over existing techniques. However, physiologically accurate 4D-CT ventilation imaging has not been achieved in patients. The purpose of this study was to evaluate 4D-CT ventilation imaging by correlating ventilation with emphysema. Emphysematous lung regions are less ventilated and can be used as surrogates for low ventilation. We tested the hypothesis: 4D-CT ventilation in emphysematous lung regions is significantly lower than in non-emphysematous regions. Four-dimensional CT ventilation images were created for 12 patients with emphysematous lung regions as observed on CT, using a total of four combinations of two deformable image registration (DIR) algorithms: surface-based (DIR(sur)) and volumetric (DIR(vol)), and two metrics: Hounsfield unit (HU) change (V(HU)) and Jacobian determinant of deformation (V(Jac)), yielding four ventilation image sets per patient. Emphysematous lung regions were detected by density masking. We tested our hypothesis using the one-tailed t-test. Visually, different DIR algorithms and metrics yielded spatially variant 4D-CT ventilation images. The mean ventilation values in emphysematous lung regions were consistently lower than in non-emphysematous regions for all the combinations of DIR algorithms and metrics. V(HU) resulted in statistically significant differences for both DIR(sur) (0.14 ± 0.14 versus 0.29 ± 0.16, p = 0.01) and DIR(vol) (0.13 ± 0.13 versus 0.27 ± 0.15, p < 0.01). However, V(Jac) resulted in non-significant differences for both DIR(sur) (0.15 ± 0.07 versus 0.17 ± 0.08, p = 0.20) and DIR(vol) (0.17 ± 0.08 versus 0.19 ± 0.09, p = 0.30). This study demonstrated the strong correlation between the HU-based 4D-CT ventilation and emphysema, which indicates the potential for HU-based 4D-CT ventilation imaging to achieve high physiologic accuracy. A further study is needed to confirm these results.

Impact of four-dimensional computed tomography pulmonary ventilation imaging-based functional avoidance for lung cancer radiotherapy.

PURPOSE: To quantify the dosimetric impact of four-dimensional computed tomography (4D-CT) pulmonary ventilation imaging-based functional treatment planning that avoids high-functional lung regions. METHODS AND MATERIALS: 4D-CT ventilation images were created from 15 non-small-cell lung cancer patients using deformable image registration and quantitative analysis of the resultant displacement vector field. For each patient, anatomic and functional plans were created for intensity-modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT). Consistent beam angles and dose-volume constraints were used for all cases. The plans with Radiation Therapy Oncology Group (RTOG) 0617-defined major deviations were modified until clinically acceptable. Functional planning spared the high-functional lung, and anatomic planning treated the lungs as uniformly functional. We quantified the impact of functional planning compared with anatomic planning using the two- or one-tailed t test. RESULTS: Functional planning led to significant reductions in the high-functional lung dose, without significantly increasing other critical organ doses, but at the expense of significantly degraded the planning target volume (PTV) conformity and homogeneity. The average reduction in the high-functional lung mean dose was 1.8 Gy for IMRT (p < .001) and 2.0 Gy for VMAT (p < .001). Significantly larger changes occurred in the metrics for patients with a larger amount of high-functional lung adjacent to the PTV. CONCLUSION: The results of the present study have demonstrated the impact of 4D-CT ventilation imaging-based functional planning for IMRT and VMAT for the first time. Our findings indicate the potential of functional planning in lung functional avoidance for both IMRT and VMAT, particularly for patients who have high-functional lung adjacent to the PTV.

Tensor grid based image registration with application to ventilation estimation on 4D CT lung data.

PURPOSE: For many image registration tasks, the information contained in the original resolution of the image data is crucial for a subsequent medical analysis, e.g. accurate assessment of local pulmonary ventilation. However, the complexity of a non-parametric registration scheme is directly connected to the resolution of the images. Therefore, the registration is often performed on a downsampled version in order to meet runtime demands and thereby producing suboptimal results. To enable the application of the highest resolution at least in regions of high clinical importance, an approach is presented replacing the usually taken equidistant grids by tensor grids for image representation. METHODS: We employ a non-parametric approach for the registration of a respiratory-gated 4D CT thorax scan. Tensor grids are introduced for the registration setting and compared to equidistant grids. For ventilation assessment, the Jacobian metric is explored. RESULTS: The application of the tensor grid approach makes the local usage of the original resolution feasible; thereby a smaller registration error is achieved in regions of higher resolution using the tensor grids, while the two types of grids perform similar in regions of equal resolution. Concerning the ventilation assessment, the Jacobian metric yields reasonable results, showing more detail using the tensor grids due to the higher resolution. CONCLUSIONS: The proposed approach using tensor grids preserves registration accuracy, while reducing computational demands. The application of the Jacobian metric for ventilation assessment in conjunction with tensor grids is promising; however, due to a missing ground-truth the medical relevance could not be established for the ventilation estimation so far.

Combined correction of recovery effect and motion blur for SUV quantification of solitary pulmonary nodules in FDG PET/CT.

OBJECTIVE: We evaluate a fully data-driven method for the combined recovery and motion blur correction of small solitary pulmonary nodules (SPNs) in F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT). METHODS: The SPN was segmented in the low-dose CT using a variable Hounsfield threshold and morphological constraints. The combined effect of limited spatial resolution and motion blur in the SPN's PET image was then modelled by an effective Gaussian point-spread function (psf). Both isotropic and non-isotropic psfs were used. To validate the method, PET/CT measurements of the NEMA/IEC spheres phantom were performed. The method was applied to 50 unselected SPNs or=30%) SUV increase in 47 SPNs (94%). CONCLUSIONS: Correction of both recovery and motion blur is mandatory for accurate SUV quantification of SPNs.