Robust CT ventilation from the integral formulation of the Jacobian

Computed tomography (CT) derived ventilation algorithms estimate the apparent voxel volume changes within an inhale/exhale CT image pair. Transformation‐based methods compute these estimates solely from the spatial transformation acquired by applying a deformable image registration (DIR) algorithm to the image pair. However, approaches based on finite difference approximations of the transformation's Jacobian have been shown to be numerically unstable. As a result, transformation‐based CT ventilation is poorly reproducible with respect to both DIR algorithm and CT acquisition method.

Purpose

We introduce a novel Integrated Jacobian Formulation (IJF) method for estimating voxel volume changes under a DIR‐recovered spatial transformation. The method is based on computing volume estimates of DIR mapped subregions using the hit‐or‐miss sampling algorithm for integral approximation. The novel approach allows for regional volume change estimates that (a) respect the resolution of the digital grid and (b) are based on approximations with quantitatively characterized and controllable levels of uncertainty. As such, the IJF method is designed to be robust to variations in DIR solutions and thus overall more reproducible.

Methods

Numerically, Jacobian estimates are recovered by solving a simple constrained linear least squares problem that guarantees the recovered global volume change is equal to the global volume change obtained from the inhale and exhale lung segmentation masks. Reproducibility of the IJF method with respect to DIR solution was assessed using the expert‐determined landmark point pairs and inhale/exhale phases from 10 four‐dimensional computed tomographies (4DCTs) available on http://www.dir-lab.com. Reproducibility with respect to CT acquisition was assessed on the 4DCT and 4D cone beam CT (4DCBCT) images acquired for five lung cancer patients prior to radiotherapy.

Results

The ten Dir‐Lab 4DCT cases were registered twice with the same DIR algorithm, but with different smoothing parameter. Finite difference Jacobian (FDJ) and IFJ images were computed for both solutions. The average spatial errors (300 landmarks per case) for the two DIR solution methods were 0.98 (1.10) and 1.02 (1.11). The average Pearson correlation between the FDJ images computed from the two DIR solutions was 0.83 (0.03), while for the IJF images it was 1.00 (0.00). For intermodality assessment, the IJF and FDJ images were computed from the 4DCT and 4DCBCT of five patients. The average Pearson correlation of the spatially aligned FDJ images was 0.27 (0.11), while it was 0.77 (0.13) for the IFJ method.

Conclusion

The mathematical theory underpinning the IJF method allows for the generation of ventilation images that are (a) computed with respect to DIR spatial accuracy on the digital voxel grid and (b) based on DIR‐measured subregional volume change estimates acquired with quantifiable and controllable levels of uncertainty. Analyses of the experiments are consistent with the mathematical theory and indicate that IJF ventilation imaging has a higher reproducibility with respect to both DIR algorithm and CT acquisition method, in comparison to the standard finite difference approach.

Quadratic penalty method for intensity-based deformable image registration and 4DCT lung motion recovery

Intensity-based deformable image registration (DIR) requires minimizing an image dissimilarity metric. Imaged anatomy, such as bones and vasculature, as well as the resolution of the digital grid, can often cause discontinuities in the corresponding objective function. Consequently, the application of a gradient-based optimization algorithm requires a preprocessing image smoothing to ensure the existence of necessary image derivatives. Simple block matching (exhaustive search) methods do not require image derivative approximations, but their general effectiveness is often hindered by erroneous solutions (outliers). Block match methods are therefore often coupled with a statistical outlier detection method to improve results.

PURPOSE

The purpose of this work is to present a spatially accurate, intensity-based DIR optimization formulation that can be solved with a straightforward gradient-free quadratic penalty algorithm and is suitable for 4D thoracic computed tomography (4DCT) registration. Additionally, a novel regularization strategy based on the well-known leave-one-out robust statistical model cross-validation method is introduced.

METHODS

The proposed Quadratic Penalty DIR (QPDIR) method minimizes both an image dissimilarity term, which is separable with respect to individual voxel displacements, and a regularization term derived from the classical leave-one-out cross-validation statistical method. The resulting DIR problem lends itself to a quadratic penalty function optimization approach, where each subproblem can be solved by straightforward block coordinate descent iteration.

RESULTS

The spatial accuracy of the method was assessed using expert-determined landmarks on ten 4DCT datasets available on www.dir-lab.com. The QPDIR algorithm achieved average millimeter spatial errors between 0.69 (0.91) and 1.19 (1.26) on the ten test cases. On all ten 4DCT test cases, the QPDIR method produced spatial accuracies that are superior or equivalent to those produced by current state-of-the-art methods. Moreover, QPDIR achieved accuracies at the resolution of the landmark error assessment (i.e., the interobserver error) on six of the ten cases.

CONCLUSION

The QPDIR algorithm is based on a simple quadratic penalty function formulation and a regularization term inspired by leave-one-out cross validation. The formulation lends itself to a parallelizable, gradient-free, block coordinate descent numerical optimization method. Numerical results indicate that the method achieves a high spatial accuracy on 4DCT inhale/exhale phases.

Technical Note: Deriving ventilation imaging from 4DCT by deep convolutional neural network

PURPOSE

Ventilation images can be derived from four-dimensional computed tomography (4DCT) by analyzing the change in HU values and deformable vector fields between different respiration phases of computed tomography (CT). As deformable image registration (DIR) is involved, accuracy of 4DCT-derived ventilation image is sensitive to the choice of DIR algorithms. To overcome the uncertainty associated with DIR, we develop a method based on deep convolutional neural network (CNN) to derive ventilation images directly from the 4DCT without explicit image registration.

METHODS

A total of 82 sets of 4DCT and ventilation images from patients with lung cancer were used in this study. In the proposed CNN architecture, the CT two-channel input data consist of CT at the end of exhale and the end of inhale phases. The first convolutional layer has 32 different kernels of size 5 × 5 × 5, followed by another eight convolutional layers each of which is equipped with an activation layer (ReLU). The loss function is the mean-squared-error (MSE) to measure the intensity difference between the predicted and reference ventilation images.

RESULTS

The predicted images were comparable to the label images of the test data. The similarity index, correlation coefficient, and Gamma index passing rate averaged over the tenfold cross validation were 0.880 ± 0.035, 0.874 ± 0.024, and 0.806 ± 0.014, respectively.

CONCLUSIONS

The results demonstrate that deep CNN can generate ventilation imaging from 4DCT without explicit deformable image registration, reducing the associated uncertainty.

Revealing full chemical forms of lead in wine with combined XRF-NMR technologies

Since 1953, The World Organization of Vine and Wine (OIV) Member States have reduced the lead maximum limits (ML) in wines, down to 0.05 mg/L (2018). Evidently, this ML value is too restrictive for wine industry as it excludes from international market a significant portion of wine production. Currently, the Codex Committee on Contaminants in Foods and OIV had recognized the value of gathering robust and novel data to better assess the best lowest ML for wine industry. Currently, there is not a direct statement within international reference documents, of which chemical form of lead must be controlled and/ or reduced. This work presents for the first time a method combining Energy Dispersive X-Ray analysis (EDAX) and Nuclear Magnetic Resonance (NMR) spectroscopies in order to determine presence and concentrations of major and trace elements of lead and other element moieties in wine that can allow to better redefine lead's ML. By identification of K, L, M, radiation shells with additional αβi labelling of lead's major and minor components with semi-quantitative XRF, combined with chemical-shift analysis of inorganic Pb4+, Pb2+ and/or organo-lead within wine samples, we propose a full discrimination framework to disentangle and quantify different chemical forms of lead.

Interim Analysis of a Two-Institution, Prospective Clinical Trial of 4DCT-Ventilation-based Functional Avoidance Radiation Therapy

PURPOSE

Functional imaging has been proposed that uses 4DCT images to calculate 4DCT-based lung ventilation (4DCT-ventilation). We have started a 2-institution, phase 2 prospective trial evaluating the feasibility, safety, and preliminary efficacy of 4DCT-ventilation functional avoidance. The trial hypothesis is that the rate of grade ≥2 radiation pneumonitis could be reduced to 12% with functional avoidance, compared with a 25% rate of pneumonitis with a historical control. The trial employed a Simon 2-stage design with a planned futility analysis after 17 evaluable patients. The purpose of this work is to present the trial design and implementation, dosimetric data, and clinical results for the planned futility analysis.

METHODS AND MATERIALS

Eligible patients were patients with lung cancer who were prescribed doses of 45 to 75 Gy. For each patient, the 4DCT data were used to generate a 4DCT-ventilation image using the Hounsfield unit technique along with a compressible flow-based image registration algorithm. Two intensity modulated radiation therapy treatment plans were generated: (1) a standard lung plan and (2) a functional avoidance treatment plan that aimed to reduce dose to functional lung while meeting target and normal tissue constraints. Patients were treated with the functional avoidance plan and evaluated for thoracic toxicity (presented as rate and 95% confidence intervals [CI]) with a 1-year follow-up.

RESULTS

The V20 to functional lung was 21.6% ± 9.5% (mean ± standard deviation) with functional avoidance, representing a decrease of 3.2% (P < .01) relative to standard, nonfunctional treatment plans. The rates of grade ≥2 and grade ≥3 radiation pneumonitis were 17.6% (95% CI, 3.8%-43.4%) and 5.9% (95% CI, 0.1%-28.7%), respectively.

CONCLUSIONS

Dosimetrically, functional avoidance achieved reduction in doses to functional lung while meeting target and organ at risk constraints. On the basis of Simon's 2-stage design and the 17.6% grade ≥2 pneumonitis rate, the trial met its futility criteria and has continued accrual.

Using 4DCT-ventilation to characterize lung function changes for pediatric patients getting thoracic radiotherapy

PURPOSE

A form of lung functional imaging has been developed that uses 4DCT data to calculate ventilation (4DCT-ventilation). Because 4DCTs are acquired as standard-of-care to manage breathing motion during radiotherapy, 4DCT-ventilation provides functional information at no extra dosimetric or monetary cost. 4DCT-ventilation has yet to be described in children. 4DCT-ventilation can be used as a tool to help assess post-treatment lung function and predict for future clinical thoracic toxicities for pediatric patients receiving radiotherapy to the chest. The purpose of this work was to perform a preliminary evaluation of 4DCT-ventilation-based lung function changes for pediatric patients receiving radiotherapy to the lungs.

METHODS

The study used four patients with pre and postradiotherapy 4DCTs. The 4DCTs, deformable image registration, and a density-change-based algorithm were used to compute pre and post-treatment 4DCT-ventilation images. The post-treatment 4DCT-ventilation images were compared to the pretreatment 4DCT-ventilation images for a global lung response and for an intrapatient dose-response (providing an assessment for dose-dependent regional dose-response).

RESULTS

For three of the four patients, a global ventilation decline of 7-37% was observed, while one patient did not demonstrate a global functional decline. Dose-response analysis did not reveal an intrapatient dose-response from 0 to 20 Gy for three patients while one patient demonstrated increased 4DCT-ventilation decline as a function of increasing lung doses up to 50 Gy.

CONCLUSIONS

Compared to adults, pediatric patients have unique lung function, dosimetric, and toxicity profiles. The presented work is the first to evaluate spatial lung function changes in pediatric patients using 4DCT-ventilation and showed lung function changes for three of the four patients. The early changes demonstrated with lung function imaging warrant further longitudinal work to determine whether the imaging-based early changes can be predicted for long-term clinical toxicity.

The DAGMAR Score: D-dimer assay-guided moderation of adjusted risk. Improving specificity of the D-dimer for pulmonary embolism

We generated a novel scoring system to improve the test characteristics of D-dimer in patients with suspected PE (pulmonary emboli). Electronic Medical Record data were retrospectively reviewed on Emergency Department (ED) patients 18 years or older for whom a D-dimer and imaging were ordered between June 4, 2012 and March 30, 2016. Symptoms (dyspnea, unilateral leg swelling, hemoptysis), age, vital signs, medical history (cancer, recent surgery, medications, history of deep vein thrombosis or PE, COPD, smoking), laboratory values (quantitative D-dimer, platelets, and mean platelet volume (MPV)), and imaging results (CT, VQ) were collected. Points were designated to factors that were significant in two multiple regression analyses, for PE or positive D-dimer. Points predictive of PE were designated positive values and points predictive of positive D-dimer, irrespective of presence of PE, were designated negative values. The DAGMAR (D-dimer Assay-Guided Moderation of Adjusted Risk) score was developed using age and platelet adjustment and points for factors associated with PE and elevated D-dimer. Of 8486 visits reviewed, 3523 were unique visits with imaging, yielding 2253 (26.5%) positive D-dimers. 3501 CT scans and 156 VQ scans were completed, detecting 198 PE. In our cohort, a DAGMAR Score < 2 equated to overall PE risk < 1.2%. Specificity improved (38% to 59%) without compromising sensitivity (94% to 96%). Use of the DAGMAR Score would have reduced CT scans from 2253 to 1556 and lead to fewer false negative results. By considering factors that affect D-dimer and also PE, we improved specificity without compromising sensitivity.

Functional-guided radiotherapy using knowledge-based planning

BACKGROUND AND PURPOSE

There 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 METHODS

A 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.

RESULTS

A 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).

CONCLUSION

The current work developed a KBP model for functional-guided radiotherapy. Modest, but statistically significant, improvements were observed in functional lung and total lung doses.

Use of the d-dimer for Detecting Pulmonary Embolism in the Emergency Department

BACKGROUND

Assessment for pulmonary embolism (PE) in the emergency department (ED) remains complex, involving clinical decision tools, blood tests, and imaging.

OBJECTIVE

Our objective was to examine the test characteristics of the high-sensitivity d-dimer for the diagnosis of PE at our institution and evaluate use of the d-dimer and factors associated with a falsely elevated d-dimer.

METHODS

We retrospectively collected data on adult patients evaluated with a d-dimer and computed tomography (CT) pulmonary angiogram or ventilation perfusion scan at two EDs between June 4, 2012 and March 30, 2016. We collected symptoms (dyspnea, unilateral leg swelling, hemoptysis), vital signs, and medical and social history (cancer, recent surgery, medications, history of deep vein thrombosis or PE, chronic obstructive pulmonary disease, smoking). We calculated test characteristics, including sensitivity, specificity, and likelihood ratios for the assay using conventional threshold and with age adjustment, and performed a univariate analysis.

RESULTS

We found 3523 unique visits with d-dimer and imaging, detecting 198 PE. Imaging was pursued on 1270 patients with negative d-dimers, revealing 9 false negatives, and d-dimer was sent on 596 patients for whom negative Pulmonary Embolism Rule-Out Criteria (PERC) were documented with 2% subsequent radiographic detection of PE. The d-dimer showed a sensitivity of 95.7% (95% confidence interval [CI] 91-98%), specificity of 40.0% (95% CI 38-42%), negative likelihood ratio of 0.11 (95% CI 0.06-0.21), and positive likelihood ratio of 1.59 (95% CI 1.53-1.66) for the radiographic detection of PE. With age adjustment, 347 of the 2253 CT scans that were pursued in patients older than 50 years with an elevated d-dimer could have been avoided without missing any additional PE. Many risk factors, such as age, history of PE, recent surgery, shortness of breath, tachycardia and hypoxia, elevated the d-dimer, regardless of the presence of PE.

CONCLUSIONS

Many patients with negative d-dimer and PERC still received imaging. Our data support the use of age adjustment, and perhaps adjustment for other factors seen in patients evaluated for PE.