4D-CT Ventilation Imaging Research Articles

Systematic Evaluation of the Impact of Lung Segmentation Methods on 4-Dimensional Computed Tomography Ventilation Imaging Using a Large Patient Database

A novel form of lung functional imaging applied for functional avoidance radiation therapy has been developed that uses 4-dimensional computed tomography (4DCT) data and image processing techniques to calculate lung ventilation (4DCT-ventilation). Lung segmentation is a common step to define a region of interest for 4DCT-ventilation generation. The purpose of this study was to quantitatively evaluate the sensitivity of 4DCT-ventilation imaging using different lung segmentation methods. The 4DCT data of 350 patients from 2 institutions were used. Lung contours were generated using 3 methods: (1) reference segmentations that removed airways and pulmonary vasculature manually (Lung-Manual), (2) standard lung contours used for planning (Lung-RadOnc), and (3) artificial intelligence (AI)-based contours that removed the airways and pulmonary vasculature (Lung-AI). The AI model was based on a residual 3-dimensional U-Net and was trained using the Lung-Manual contours of 279 patients. We compared the Lung-RadOnc or Lung-AI with Lung-Manual contours for the entire 4DCT-ventilation functional avoidance process including lung segmentation (surface Dice similarity coefficient [Surface DSC]), 4DCT-ventilation generation (correlation), and subanalysis of 10 patients on a dosimetric endpoint (percentage of high functional volume of lung receiving ≥20 Gy [fV20{%}]). Surface DSC comparing Lung-Manual/Lung-RadOnc and Lung-Manual/Lung-AI contours was 0.40 ± 0.06 and 0.86 ± 0.04, respectively. The correlation between 4DCT-ventilation images generated with Lung-Manual/Lung-RadOnc and Lung-Manual/Lung-AI were 0.48 ± 0.14 and 0.85 ± 0.14, respectively. The difference in fV20[%] between 4DCT-ventilation generated with Lung-Manual/Lung-RadOnc and Lung-Manual/Lung-AI was 2.5% ± 4.1% and 0.3% ± 0.5%, respectively. Our work showed that using standard planning lung contours can result in significantly variable 4DCT-ventilation images. The study demonstrated that AI-based segmentations generate lung contours and 4DCT-ventilation images that are similar to those generated using manual methods. The significance of the study is that it characterizes the lung segmentation sensitivity of the 4DCT-ventilation process and develops methods that can facilitate the integration of this novel imaging in busy clinics.

A\xa0novel lung-avoidance planning strategy based on 4DCT ventilation imaging and CT density characteristics for stage\xa0III non-small-cell lung cancer patients

BackgroundFunctional planning based merely on 4DCT ventilation imaging has limitations. In this study, we proposed a radiotherapy planning strategy based on 4DCT ventilation imaging and CT density characteristics.Materials and methodsFor 20 stage III non-small-cell lung cancer (NSCLC) patients, clinical plans and lung-avoidance plans were generated. Through deformable image registration (DIR) and quantitative image analysis, a 4DCT ventilation map was calculated. High-, medium-, and low-ventilation regions of the lung were defined based on the ventilation value. In addition, the total lung was also divided into high-, medium-, and low-density areas according to the HU threshold. The lung-avoidance plan aimed to reduce the dose to functional and high-density lungs while meeting standard target and critical structure constraints. Standard and dose–function metrics were compared between the clinical and lung-avoidance plans.ResultsLung avoidance plans led to significant reductions in high-function and high-density lung doses, without significantly increasing other organ at risk (OAR) doses, but at the expense of a significantly degraded homogeneity index (HI) and conformity index (CI; p < 0.05) of the planning target volume (PTV) and a slight increase in monitor units (MU) as well as in the number of segments (p > 0.05). Compared with the clinical plan, the mean lung dose (MLD) in the high-function and high-density areas was reduced by 0.59 Gy and 0.57 Gy, respectively.ConclusionA lung-avoidance plan based on 4DCT ventilation imaging and CT density characteristics is feasible and implementable, with potential clinical benefits. Clinical trials will be crucial to show the clinical relevance of this lung-avoidance planning strategy.

4DCT Ventilation Map Construction Using Biomechanics-base Image Registration and Enhanced Air Segmentation.

Current lung radiation therapy (RT) treatment planning algorithms used in most centers assume homogeneous lung function. However, co-existing pulmonary dysfunctions present in many non-small cell lung cancer (NSCLC) patients, particularly smokers, cause regional variations in both perfusion and ventilation, leading to inhomogeneous lung function. An adaptive RT treatment planning that deliberately avoids highly functional lung regions can potentially reduce pulmonary toxicity and morbidity. The ventilation component of lung function can be measured using a variety of techniques. Recently, 4DCT ventilation imaging has emerged as a cost-effective and accessible method. Current 4DCT ventilation calculation methods, including the intensity-based and Jacobian models, suffer from inaccurate estimations of air volume distribution and unreliability of intensity-based image registration algorithms. In this study, we propose a novel method that utilizes a biomechanical model-based registration along with an accurate air segmentation algorithm to calculate 4DCT ventilation maps. The results show a successful development of ventilation maps using the proposed method.

Dosimetric feasibility of 4DCT-ventilation imaging guided proton therapy for locally advanced non-small-cell lung cancer

BackgroundThe principle aim of this study is to incorporate 4DCT ventilation imaging into functional treatment planning that preserves high-functioning lung with both double scattering and scanning beam techniques in proton therapy.MethodsEight patients with locally advanced non-small-cell lung cancer were included in this study. Deformable image registration was performed for each patient on their planning 4DCTs and the resultant displacement vector field with Jacobian analysis was used to identify the high-, medium- and low-functional lung regions. Five plans were designed for each patient: a regular photon IMRT vs. anatomic proton plans without consideration of functional ventilation information using double scattering proton therapy (DSPT) and intensity modulated proton therapy (IMPT) vs. functional proton plans with avoidance of high-functional lung using both DSPT and IMPT. Dosimetric parameters were compared in terms of tumor coverage, plan heterogeneity, and avoidance of normal tissues.ResultsOur results showed that both DSPT and IMPT plans gave superior dose advantage to photon IMRTs in sparing low dose regions of the total lung in terms of V5 (volume receiving 5Gy). The functional DSPT only showed marginal benefit in sparing high-functioning lung in terms of V5 or V20 (volume receiving 20Gy) compared to anatomical plans. Yet, the functional planning in IMPT delivery, can further reduce the low dose in high-functioning lung without degrading the PTV dosimetric coverages, compared to anatomical proton planning. Although the doses to some critical organs might increase during functional planning, the necessary constraints were all met.ConclusionsIncorporating 4DCT ventilation imaging into functional proton therapy is feasible. The functional proton plans, in intensity modulated proton delivery, are effective to further preserve high-functioning lung regions without degrading the PTV coverage.

Functional-guided radiotherapy using knowledge-based planning

Background and purposeThere are two significant challenges when implementing functional-guided radiotherapy using 4DCT-ventilation imaging: (1) lack of knowledge of realistic patient specific dosimetric goals for functional lung and (2) ensuring consistent plan quality across multiple planners. Knowledge-based planning (KBP) is positioned to address both concerns. Material and methodsA KBP model was created from 30 previously planned functional-guided lung patients. Standard organs at risk (OAR) in lung radiotherapy and a ventilation contour delineating areas of high ventilation were included. Model validation compared dose-metrics to standard OARs and functional dose-metrics from 20 independent cases that were planned with and without KBP. ResultsA significant improvement was observed for KBP optimized plans in V20Gy and mean dose to functional lung (p = 0.005 and 0.001, respectively), V20Gy and mean dose to total lung minus GTV (p = 0.002 and 0.01, respectively), and mean doses to esophagus (p = 0.005). ConclusionThe current work developed a KBP model for functional-guided radiotherapy. Modest, but statistically significant, improvements were observed in functional lung and total lung doses.

Evaluating Which Dose-Function Metrics Are Most Critical for Functional Guided Radiation Therapy with CT Ventilation Imaging

4DCT-ventilation imaging is increasingly being used to calculate lung ventilation and implement functional guided radiotherapy in clinical trials. There has been little exhaustive work evaluating which dose-function metrics should be used for treatment planning and plan evaluation for functional guided radiotherapy. Our study evaluated which dose-function metrics are most critical in assessing the risk of radiation pneumonitis (RP). Seventy lung cancer patients with 4DCT imaging and RP grading were used. Pre-treatment 4DCTs of each patient were used to calculate ventilation images. We evaluated 3 different types of dose function metrics that combined that patient’s 4DCT-ventilation image and treatment planning dose distribution: 1) structure-based approaches 2) image-based approaches using the dose-function histogram (DFH) and 3) non-linear weighting schemes. Structure-based approaches used a binary approximation in which the lung was binned to either functional or non-functional status. A full range of cutoff values to delineate between functional and non-functional and the volume of functional lung receiving ≥ 5Gy, 10Gy, 20Gy, and 30Gy was investigated. Imaging-based and non-linear approaches investigated the fraction of lung function receiving ≥ 5Gy, 10Gy, 20Gy, and 30Gy. Maximum likelihood methods were used to generate normal tissue complication probability (NTCP) models predicting grade 3+ RP for the dose-function schemes and all tested dose-function metrics. The area under the curve (AUC) for each model was used to quantify the ability to predict for toxicity. All techniques were compared to NTCP models based on traditional, total lung dose metrics. The most predictive models for grade 3+ RP were structure-based approaches that focused on the volume of functional lung receiving ≥20Gy (AUC=0.70) where functional lung was treated as regions with ventilation values ≥84th percentile. Imaging-based analysis with the DFH and non-linear weighted ventilation values yielded AUCs of 0.66 and 0.67, respectively, when evaluating the fraction of functionality receiving ≥20Gy. All dose-function metrics outperformed the traditional lung dose metrics (mean lung dose, AUC = 0.55). A full range of dose-function metrics and functional thresholds were examined. The AUC values for the most predictive functional models occupied a narrow range (0.66-0.70) and all demonstrated improvements over AUC from traditional lung dose metrics (0.55). Identifying the dose-function parameters most predictive of grade 3+ RP provides valuable data for treatment planning and plan evaluation parameters. With prospective clinical trials of functional guided radiotherapy using 4DCT-ventilation imaging underway, this work provides seminal data to help establish guidelines for the implementation of functional guided radiotherapy.

Regional Lung Function Profiles of Stage I and III Lung Cancer Patients: An Evaluation for Functional Avoidance Radiation Therapy

The development of clinical trials is underway to use 4-dimensional computed tomography (4DCT) ventilation imaging to preferentially spare functional lung in patients undergoing radiation therapy. The purpose of this work was to generate data to aide with clinical trial design by retrospectively characterizing dosimetric and functional profiles for patients with different stages of lung cancer. A total of 118 lung cancer patients (36% stage I and 64% stage III) from 2 institutions were used for the study. A 4DCT-ventilation map was calculated using the patient's 4DCT imaging, deformable image registration, and a density-change-based algorithm. To assess each patient's spatial ventilation profile both quantitative and qualitative metrics were developed, including an observer-based defect observation and metrics based on the ventilation in each lung third. For each patient we used the clinical doses to calculate functionally weighted mean lung doses and metrics that assessed the interplay between the spatial location of the dose and high-functioning lung. Both qualitative and quantitative metrics revealed a significant difference in functional profiles between the 2 stage groups (P<.01). We determined that 65% of stage III and 28% of stage I patients had ventilation defects. Average functionally weighted mean lung dose was 19.6Gy and 5.4Gy for stage III and I patients, respectively, with both groups containing patients with large spatial overlap between dose and high-function regions. Our 118-patient retrospective study found that 65% of stage III patients have regionally variant ventilation profiles that are suitable for functional avoidance. Our results suggest that regardless of disease stage, it is possible to have unique spatial interplay between dose and high-functional lung, highlighting the importance of evaluating the function of each patient and developing a personalized functional avoidance treatment approach.

Analysis of Long-Term 4-Dimensional Computed Tomography Regional Ventilation After Radiation Therapy

To determine whether regional ventilation, as measured using 4-dimensional computed tomography (4D-CT), declines after radiation therapy (RT). We analyzed pretreatment 4D-CT scans associated with 2 RT courses. We quantified regional pulmonary function over equivalent dose in 2 Gy (EQD2α/β=3) intervals of 0 to 5 Gy, 5 to 20 Gy, 20 to 40 Gy, and >40 Gy using percentile-normalized intensity-based (VentInt) and Jacobian-based (VentJac) ventilation metrics. We modeled the impact of dose on mean ventilation (Vent¯) and regional tidal volume (rTV: tidal volume [TV] within a dose interval normalized to total lung TV). We also identified clinical and dosimetric factors that affected regional ventilation changes (ΔVent¯ and ΔrTV) after RT for the >20 Gy dose interval. After RT, Vent¯Int exhibited statistically significant dose-dependent declines within the 20 to 40 Gy (-5.0%; P=.03) and >40 Gy (-6.8%; P<.01) intervals. Vent¯Jac exhibited a declining trend after RT only for the >40 Gy interval (-4.6%; P=.07). Factors associated with ΔVent¯Int for the >20 Gy dose interval included airway stenosis progression (P=.03) and gross tumor volume (P=.09). Both rTVInt and rTVJac were associated with small (<2%) but significant declines after RT for 20 to 40 Gy and >40 Gy intervals. Factors associated with declining rTVInt (P<.05) for the >20 Gy dose interval included airway stenosis progression, greater V20 (volume of lung receiving >20 Gy), and smaller fraction of emphysema in V20. The association between the absence of chronic obstructive pulmonary disease and declining rTV trended toward significance (P=.09). Regional ventilation, as measured using 4D-CT, demonstrates a dose-dependent decline after RT. Our results support the use of 4D-CT ventilation imaging for monitoring regional pulmonary function change after RT.

Can 4D-CT Ventilation Imaging Replace Technegas V-SPECT for Functionally Adaptive Radiation Therapy? First Results

Four-dimensional-CT ventilation imaging (CT-VI) is a novel method for imaging regional air volume changes in the lung. Previous attempts at comparing CT-VI and DTPA V-SPECT have shown poor results due to “clumping” of DTPA in large airways. Technegas is a smaller molecule than DTPA, and disperses throughout normal lung with less clumping and no washout. In this work we perform the first comparison of Technegas V-SPECT and CT-VI. We test the impact of two different CT ventilation metrics, and two different methods (algorithm- or clinician-based) for defining functional lung.

Utilization of Hypofractionated Regimens for Treatment of Breast Cancer in an Insured Population Before and After Initiation of ASTRO’s “Choosing Wisely” Campaign

the group with noted ventilation defects had a lower FEV1 (55%) than the group with no noted defects (68%) (p Z 0.07). Conclusions: Validation of 4DCT ventilation maps with clinically relevant metrics is essential. Our data demonstrate good agreement between PFTs and ventilation data, indicating that 4DCT ventilation can reliably demonstrate oncologic-based obstructive lung disease. The 4DCT-ventilation imaging enables exciting opportunities to assess pre-treatment lung function and create functional avoidance radiation therapy plans using the patient’s simulation data. The current work presents an important step for the integration of 4DCT-ventilation into clinical practice. Author Disclosure: Y. Vinogradskiy: None. L. Schubert: None. D. Brennan: None. R. Castillo: E. Research Grant; NIH. E. Castillo: E. Research Grant; NIH. T. Guerrero: E. Research Grant; NIH. M. Miften: None. B. Kavanagh: None. M.K. Mary: None.

Pulmonary Ventilation Imaging Based on 4-Dimensional Computed Tomography: Comparison With Pulmonary Function Tests and SPECT Ventilation Images

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. 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. 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). 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.

TH‐E‐BRF‐02: 4D‐CT Ventilation Image‐Based IMRT Plans Are Dosimetrically Comparable to SPECT Ventilation Image‐Based Plans

Purpose:An emerging lung ventilation imaging method based on 4D‐CT can be used in radiotherapy to selectively avoid irradiating highly‐functional lung regions, which may reduce pulmonary toxicity. Efforts to validate 4DCT ventilation imaging have been focused on comparison with other imaging modalities including SPECT and xenon CT. The purpose of this study was to compare 4D‐CT ventilation image‐based functional IMRT plans with SPECT ventilation image‐based plans as reference.Methods:4D‐CT and SPECT ventilation scans were acquired for five thoracic cancer patients in an IRB‐approved prospective clinical trial. The ventilation images were created by quantitative analysis of regional volume changes (a surrogate for ventilation) using deformable image registration of the 4D‐CT images. A pair of 4D‐CT ventilation and SPECT ventilation image‐based IMRT plans was created for each patient. Regional ventilation information was incorporated into lung dose‐volume objectives for IMRT optimization by assigning different weights on a voxel‐by‐voxel basis. The objectives and constraints of the other structures in the plan were kept identical. The differences in the dose‐volume metrics have been evaluated and tested by a paired t‐test. SPECT ventilation was used to calculate the lung functional dose‐volume metrics (i.e., mean dose, V20 and effective dose) for both 4D‐CT ventilation image‐based and SPECT ventilation image‐based plans.Results:Overall there were no statistically significant differences in any dose‐volume metrics between the 4D‐CT and SPECT ventilation imagebased plans. For example, the average functional mean lung dose of the 4D‐CT plans was 26.1±9.15 (Gy), which was comparable to 25.2±8.60 (Gy) of the SPECT plans (p = 0.89). For other critical organs and PTV, nonsignificant differences were found as well.Conclusion:This study has demonstrated that 4D‐CT ventilation image‐based functional IMRT plans are dosimetrically comparable to SPECT ventilation image‐based plans, providing evidence to use 4D‐CT ventilation imaging for clinical applications.Supported in part by Free to Breathe Young Investigator Research Grant and NIH/NCI R01 CA 093626. The authors thank Philips Radiation Oncology Systems for the Pinnacle3 treatment planning systems

Comparison of 4-Dimensional Computed Tomography Ventilation With Nuclear Medicine Ventilation-Perfusion Imaging: A Clinical Validation Study

Four-dimensional computed tomography (4DCT) ventilation imaging provides lung function information for lung cancer patients undergoing radiation therapy. Before 4DCT-ventilation can be implemented clinically it needs to be validated against an established imaging modality. The purpose of this work was to compare 4DCT-ventilation to nuclear medicine ventilation, using clinically relevant global metrics and radiologist observations. Fifteen lung cancer patients with 16 sets of 4DCT and nuclear medicine ventilation-perfusion (VQ) images were used for the study. The VQ-ventilation images were acquired in planar mode using Tc-99m-labeled diethylenetriamine-pentaacetic acid aerosol inhalation. 4DCT data, spatial registration, and a density-change-based model were used to compute a 4DCT-based ventilation map for each patient. The percent ventilation was calculated in each lung and each lung third for both the 4DCT and VQ-ventilation scans. A nuclear medicine radiologist assessed the VQ and 4DCT scans for the presence of ventilation defects. The VQ and 4DCT-based images were compared using regional percent ventilation and radiologist clinical observations. Individual patient examples demonstrate good qualitative agreement between the 4DCT and VQ-ventilation scans. The correlation coefficients were 0.68 and 0.45, using the percent ventilation in each individual lung and lung third, respectively. Using radiologist-noted presence of ventilation defects and receiver operating characteristic analysis, the sensitivity, specificity, and accuracy of the 4DCT-ventilation were 90%, 64%, and 81%, respectively. The current work compared 4DCT with VQ-based ventilation using clinically relevant global metrics and radiologist observations. We found good agreement between the radiologist's assessment of the 4DCT and VQ-ventilation images as well as the percent ventilation in each lung. The agreement lessened when the data were analyzed on a regional level. Our study presents an important step for the integration of 4DCT-ventilation into thoracic clinical practice.

TH-A-WAB-03: Radiation Dose Changes Pulmonary Function Measured by 4D-CT Ventilation Imaging

Purpose: The purpose of this study was to quantify mid‐and post‐treatment changes in 4D‐CT ventilation and test the hypothesis: temporal changes of 4D‐CT ventilation in lung regions receiving high doses are greater than those in regions receiving low or no doses. Methods: In an IRB‐approved clinical trial, repeat 4D‐CT scans were acquired for eight thoracic cancer patients treated with conventionally‐fractionated or hypo‐fractionated radiotherapy at the following time points: pre‐treatment (8 patients), mid‐treatment (6) and post‐treatment (7). Ventilation images were created for each time point using deformable registration for spatial mapping of the peak‐exhale 4D‐CT image to the peak‐inhale image and computation of Jacobian‐based ventilation metric. To quantify the ventilation change between pre‐treatment (baseline) and mid‐or post‐treatment, rigid registration was performed and the ventilation values were normalized by the mean value in high‐functional (>50th percentile ventilation value) lung regions receiving low doses (biologically effective dose <30 Gy). Statistical significance was tested using a Wilcoxon test. Results: Absolute ventilation changes in the high dose ROI were found to be greater than those in the low dose ROI consistently for all patients at all time points, except for one case. Overall, the mean absolute ventilation change in the high dose ROI was 22.6±17.7%, which was significantly greater than that in the low dose ROI (5.0±3.7%) (p<0.01). Several patients showed clear correlations between 4D‐CT ventilation changes and anatomic changes observed in CT images. For example, patient 3 demonstrated increased ventilation, which was correlated with central airway re‐opening and tumor regression. Conclusion: An 8‐patient study demonstrated significantly greater changes of 4D‐CT ventilation in lung regions receiving high doses than those in regions receiving low or no doses, providing a validation for 4D‐CT ventilation imaging. Future studies will focus on detailed analysis of correlations between 4D‐CT ventilation changes and anatomic changes. National Lung Cancer Partnership Young Investigator Research Grant; NIH/NCI2 R01 CA 093626

SU-D-BRB-01: 4D-CT Lung Ventilation Images Vary with 4D-CT Sorting Techniques.

4D-CT ventilation imaging is a novel promising technique for lung functional imaging and has potential as a biomarker for radiation pneumonitis, but has not been validated in human subjects. The current 4D- CT technique with phase-based sorting results in artifacts at an alarmingly high frequency (90%), which may introduce variations into ventilation calculations. The purpose of this study was to quantify the variability of 4D- CT ventilation imaging to 4D-CT sorting techniques. Two 4D-CT images were generated from the same data set by: (1) phase-based; (2) anatomic similarity- and abdominal displacement-based sorting for five patients. Two ventilation image sets (V_phase and V_anat) were then calculated by deformable image registration of peak-exhale and peak-inhale4D-CT images and quantification of regional volume change based on Hounsfield unit change. The variability of 4D-CT ventilation imaging wasquantified using the voxel-based Spearman rank correlation coefficients and Dice similarity coefficients (DSC) for the spatial overlap of segmented low- functional lung regions. The relationship between the abdominal motionrange variation and ventilation variation was also assessed using linearregression. Furthermore, the correlations between V_phase or V_anat and SPECT ventilation images (assumed ground-truth) were compared. In general, displacement- and anatomic similarity-based sorting reduced 4D- CT artifacts compared to phase-based sorting. The voxel-based correlationsbetween V_phase and V_anat were only moderate (range, 0.57-0.77). The DSCs for the low-functional lung regions were moderate to substantial (0.58-0.70). The relationship between the motion range variation and ventilation variation was strong on average (R2=0.79±0.25), suggesting that ventilation variations are related to 4D-CT artifacts. Vanat was found to improve correlations with SPECT ventilation images compared to V_phase. 4D-CT ventilation images vary markedly with 4D-CT sorting techniques. 4D-CT artifacts should be considered as a significant source of variation in 4D-CT ventilation imaging during its validation. This study wassupported in part by NIH/NCI R01 93626. SK and CL are employees ofPhilips Research.

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 (DIRsur) and volumetric (DIRvol), and two metrics: Hounsfield unit (HU) change (VHU) and Jacobian determinant of deformation (VJac), 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. VHU resulted in statistically significant differences for both DIRsur (0.14 ± 0.14 versus 0.29 ± 0.16, p = 0.01) and DIRvol (0.13 ± 0.13 versus 0.27 ± 0.15, p < 0.01). However, VJac resulted in non-significant differences for both DIRsur (0.15 ± 0.07 versus 0.17 ± 0.08, p = 0.20) and DIRvol (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.

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

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. 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. 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. 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.