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PDF file, 332KB, Immunoblotting for cleaved PARP 24 hours after radiation treatment, PD0325901, and API-2 treatment to detect activation of apoptotic pathways.

Supplemental Figure 2

PDF file, 41KB, Changes in weight during the study period for the mice randomized to the eight treatment groups described.

PDF file, 48KB, Changes in MRI tumor volume for mice treated with radiation alone, API-2, or radiation with API-2. There was no radiosensitization observed with API-2 in the absence of a MEK inhibitor.

PDF file, 327KB, Treatment of MIA-PaCa-2 cells with API-2 induces potent inhibition of Akt activation at 1 hour, regardless of the presence of PD0325901.

PDF file, 318KB, Dose dependency of PD0325901 in multiple cell lines. Treatment with PD0325901 induces potent inhibition of pERK-1/2 levels at one and three hours.

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There is an urgent need for the development of novel therapies to treat pancreatic cancer, which is among the most lethal of all cancers. KRAS-activating mutations, which are found in more than 90% of pancreatic adenocarcinomas, drive tumor dependency on the Ras/MAPK and Akt signaling pathways. Radiation is currently being explored as a component of the standard treatment regimen for pancreatic cancer. This study's purpose was to test the hypothesis that MAP kinase kinase (MEK or MAP2K) inhibitors will offer clear therapeutic benefit when integrated into radiotherapy treatment regimens for treatment of this disease. We explored the activation of the mitogen-activated protein kinase (MAPK) and Akt pathways in response to radiation in multiple pancreatic tumor cell lines. Small molecule inhibitors of MEK (PD0325901) and Akt (API-2) were subsequently evaluated for their radiosensitizing potential alone and in combination. In vivo efficacy was tested in subcutaneous MIA-PaCa2 xenografts. Phosphorylated levels of extracellular signal–regulated kinase (ERK)-1/2 and Akt were found to increase in response to radiation treatment in our pancreatic tumor cell line panel. MEK inhibitor–induced radiosensitization was observed in vitro and in vivo. The further addition of an Akt inhibitor to the MEK inhibitor/radiation regimen resulted in enhanced therapeutic gain as determined by increased radiosensitization and tumor cell death. In conclusion, MEK inhibition results in growth arrest, apoptosis, and radiosensitization of multiple preclinical pancreatic tumor models, and the effects can be enhanced by combination with an Akt inhibitor. These results provide rationale for further testing of a treatment regimen in pancreatic cancer that combines MEK inhibition with radiation, optimally in conjunction with Akt inhibition. Mol Cancer Ther; 11(5); 1193–202. ©2012 AACR.

Chronic obstructive pulmonary disease (COPD) is heterogenous in its clinical manifestations and disease progression. Patients often have disease courses that are difficult to predict with readily available data, such as lung function testing. The ability to better classify COPD into well-defined groups will allow researchers and clinicians to tailor novel therapies, monitor their effects, and improve patient-centered outcomes. Different modalities of assessing these COPD phenotypes are actively being studied, and an area of great promise includes the use of quantitative computed tomography (QCT) techniques focused on key features such as airway anatomy, lung density, and vascular morphology. Over the last few decades, companies around the world have commercialized automated CT software packages that have proven immensely useful in these endeavors. This article reviews the key features of several commercial platforms, including the technologies they are based on, the metrics they can generate, and their clinical correlations and applications. While such tools are increasingly being used in research and clinical settings, they have yet to be consistently adopted for diagnostic work-up and treatment planning, and their full potential remains to be explored.

Purpose Recent advancements in functional lung imaging have been developed to improve clinicians’ knowledge of patient pulmonary condition prior to treatment. Ultimately, it may be possible to employ these functional imaging modalities to tailor radiation treatment plans to optimize patient outcome and mitigate pulmonary complications. Parametric response mapping (PRM) is a computed tomography (CT)–based functional lung imaging method that utilizes a voxel‐wise image analysis technique to classify lung abnormality phenotypes, and has previously been shown to be effective at assessing lung complication risk in diagnostic applications. The purpose of this work was to demonstrate the implementation of PRM guidance in radiotherapy treatment planning. Methods and materials A retrospective study was performed with 18 lung cancer patients to test the incorporation of PRM into a radiotherapy planning workflow. Paired inspiration/expiration pretreatment CT scans were acquired and PRM analysis was utilized to classify each voxel as normal, parenchymal disease, small airway disease, and emphysema. Density maps were generated for each PRM classification to contour high density regions of pulmonary abnormalities. Conventional volumetric‐modulated arc therapy and PRM‐guided treatment plans were designed for each patient. Results PRM guidance was successfully implemented into the treatment planning process. The inclusion of PRM priorities resulted in statistically significant (p

Background Lung cancer risk prediction models do not routinely incorporate imaging metrics available on low-dose CT (LDCT) imaging of the chest ordered for lung cancer screening. Research Question What is the association between quantitative emphysema measured on LDCT imaging and lung cancer incidence and mortality, all-cause mortality, and airflow obstruction in individuals who currently or formerly smoked and are undergoing lung cancer screening? Study Design and Methods In 7,262 participants in the CT arm of the National Lung Screening Trial, percent low attenuation area (%LAA) was defined as the percentage of lung volume with voxels less than –950 Hounsfield units on the baseline examination. Multivariable Cox proportional hazards models, adjusting for competing risks where appropriate, were built to test for association between %LAA and lung cancer incidence, lung cancer mortality, and all-cause mortality with censoring at 6 years. In addition, multivariable logistic regression models were built to test the cross-sectional association between %LAA and airflow obstruction on spirometry, which was available in 2,700 participants. Results The median %LAA was 0.8% (interquartile range, 0.2%-2.7%). Every 1% increase in %LAA was independently associated with higher hazards of lung cancer incidence (hazard ratio [HR], 1.02; 95% CI, 1.01-1.03; P = .004), lung cancer mortality (HR, 1.02; 95% CI, 1.00-1.05; P = .045), and all-cause mortality (HR, 1.01; 95% CI, 1.00-1.03; P = .042). Among participants with spirometry, 892 had airflow obstruction. The likelihood of airflow obstruction increased with every 1% increase in %LAA (odds ratio, 1.07; 95% CI, 1.06-1.09; P 65 years. Interpretation Quantitative emphysema measured on LDCT imaging of the chest can be leveraged to improve lung cancer risk prediction and help diagnose COPD in individuals who currently or formerly smoked and are undergoing lung cancer screening.

Background: Little is known about factors associated with emphysema progression in cigarette smokers. We evaluated factors associated with change in emphysema and forced expiratory volume in 1 second (FEV(1)) in participants with and without chronic obstructive pulmonary disease (COPD). Methods: This retrospective study included individuals participating in the COPD Genetic Epidemiology study who completed the 5-year follow-up, including inspiratory and expiratory computed tomography (CT) and spirometry. All paired CT scans were analyzed using micro-mapping, which classifies individual voxels as emphysema or functional small airway disease (fSAD). Presence and progression of emphysema and FEV(1) were determined based on comparison to nonsmoker values. Logistic regression analyses were used to identify clinical parameters associated with disease progression. Results: A total of 3088 participants were included with a mean ± SD age of 60.7±8.9 years, including 72 nonsmokers. In all Global initiative for chronic Obstructive Lung Disease (GOLD) stages, the presence of emphysema at baseline was associated with emphysema progression (odds ratio [OR]: GOLD 0: 4.32; preserved ratio-impaired spirometry [PRISm]; 5.73; GOLD 1: 5.16; GOLD 2: 5.69; GOLD 3/4: 5.55; all p ≤0.01). If there was no emphysema at baseline, the amount of fSAD at baseline was associated with emphysema progression (OR for 1% increase: GOLD 0: 1.06; PRISm: 1.20; GOLD 1: 1.7; GOLD 3/4: 1.08; all p ≤ 0.03).In 1735 participants without spirometric COPD, progression in emphysema occurred in 105 (6.1%) participants and only 21 (1.2%) had progression in both emphysema and FEV(1). Conclusions: The presence of emphysema is an important predictor of emphysema progression. In patients without emphysema, fSAD is associated with the development of emphysema. In participants without spirometric COPD, emphysema progression occurred independently of FEV(1) decline.

Parametric response mapping (PRM) is a novel computed tomography (CT) technology that has shown potential for assessment of bronchiolitis obliterans syndrome (BOS) after hematopoietic stem cell transplantation (HCT). The primary aim of this study was to evaluate whether variations in image acquisition under real-world conditions affect the PRM measurements of clinically diagnosed BOS. CT scans were obtained retrospectively from 72 HCT recipients with BOS and graft-versus-host disease from Fred Hutchinson Cancer Research Center, Karolinska Institute, and the University of Michigan. Whole lung volumetric scans were performed at inspiration and expiration using site-specific acquisition and reconstruction protocols. PRM and pulmonary function measurements were assessed. Patients with moderately severe BOS at diagnosis (median forced expiratory volume at 1 second [FEV1] 53.5% predicted) had similar characteristics between sites. Variations in site-specific CT acquisition protocols had a negligible effect on the PRM-derived small airways disease (SAD), that is, BOS measurements. PRM-derived SAD was found to correlate with FEV1% predicted and FEV1/ forced vital capacity (R = -0.236, P = .046; and R = -0.689, P < .0001, respectively), which suggests that elevated levels in the PRM measurements are primarily affected by BOS airflow obstruction and not CT scan acquisition parameters. Based on these results, PRM may be applied broadly for post-HCT diagnosis and monitoring of BOS.

Parametric response mapping (PRM) is a computed tomography (CT)-based method to phenotype patients with chronic obstructive pulmonary disease (COPD). It is capable of differentiating emphysema-related air trapping with nonemphysematous air trapping (small airway disease), which helps to identify the extent and localization of the disease. Most studies evaluating the gene expression in smokers and COPD patients related this to spirometric measurements, but none have investigated the relationship with CT-based measurements of lung structure. The current study aimed to examine gene expression profiles of brushed bronchial epithelial cells in association with the PRM-defined CT-based measurements of emphysema (PRMEmph) and small airway disease (PRMfSAD). Using the Top Institute Pharma (TIP) study cohort (COPD = 12 and asymptomatic smokers = 32), we identified a gene expression signature of bronchial brushings, which was associated with PRMEmph in the lungs. One hundred thirty-three genes were identified to be associated with PRMEmph. Among the most significantly associated genes, CXCL11 is a potent chemokine involved with CD8+ T cell activation during inflammation in COPD, indicating that it may play an essential role in the development of emphysema. The PRMEmph signature was then replicated in two independent data sets. Pathway analysis showed that the PRMEmph signature is associated with proinflammatory and notch signaling pathways. Together these findings indicate that airway epithelium may play a role in the development of emphysema and/or may act as a biomarker for the presence of emphysema. In contrast, its role in relation to functional small airways disease is less clear.

Chronic rejection of lung allografts has two major subtypes, bronchiolitis obliterans syndrome (BOS) and restrictive allograft syndrome (RAS), which present radiologically either as air trapping with small airways disease or with persistent pleuroparenchymal opacities. Parametric response mapping (PRM), a computed tomography (CT) methodology, has been demonstrated as an objective readout of BOS and RAS and bears prognostic importance, but has yet to be correlated to biological measures. Using a topological technique, we evaluate the distribution and arrangement of PRM-derived classifications of pulmonary abnormalities from lung transplant recipients undergoing redo-transplantation for end-stage BOS (N = 6) or RAS (N = 6). Topological metrics were determined from each PRM classification and compared to structural and biological markers determined from microCT and histopathology of lung core samples. Whole-lung measurements of PRM-defined functional small airways disease (fSAD), which serves as a readout of BOS, were significantly elevated in BOS versus RAS patients (p = 0.01). At the core-level, PRM-defined parenchymal disease, a potential readout of RAS, was found to correlate to neutrophil and collagen I levels (p < 0.05). We demonstrate the relationship of structural and biological markers to the CT-based distribution and arrangement of PRM-derived readouts of BOS and RAS. ispartof: CELLS vol:11 issue:4 ispartof: location:Switzerland status: published

Rationale: Evidence suggests damage to small airways is a key pathologic lesion in chronic obstructive pulmonary disease (COPD). Computed tomography densitometry has been demonstrated to identify e...

Background: Asthma is a disease characterized by ventilation heterogeneity (VH). A number of studies have demonstrated that VH markers derived by using impulse oscillometry (IOS) or multiple-breath washout (MBW) are associated with key asthmatic patient related outcome measures and airways hyperresponsiveness. However, the topographical mechanisms of VH in the lung remain poorly understood.Objectives: We hypothesized that specific regionalization of topographical small-airway disease would best account for IOS- and MBW-measured indices in patients.Methods: We evaluated the results of paired expiratory/inspiratory computed tomography in a cohort of asthmatic (n = 41) and healthy (n = 11) volunteers to understand the determinants of clinical VH indices commonly reported by using IOS and MBW. Parametric response mapping (PRM) was used to calculate the functional small-airways disease marker PRMfSAD and Hounsfield unit (HU)-based density changes from total lung capacity to functional residual capacity (Delta HU); gradients of Delta HU in gravitationally perpendicular (parallel) inferior-superior (anterior-posterior) axes were quantified.Results: The Delta HU gradient in the inferior-superior axis provided the highest level of discrimination of both acinar VH (measured by using phase 3 slope analysis of multiple-breath washout data) and resistance at 5 Hz minus resistance at 20 Hz measured by using impulse oscillometry (R5-R20) values. Patients with a high inferior-superior Delta HU gradient demonstrated evidence of reduced specific ventilation in the lower lobes of the lungs and high levels of PRMfSAD. A computational small-airway tree model confirmed that constriction of gravitationally dependent, lower-zone, small airway branches would promote the largest increases in R5-R20 values. Ventilation gradients correlated with asthma control and quality of life but not with exacerbation frequency.Conclusions: Lower lobe predominant small-airways disease is a major driver of clinically measured VH in adults with asthma.

The Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study, which began in 2007, is an ongoing multicenter observational cohort study of more than 10,000 current and former smokers. The study is aimed at understanding the etiology, progression, and heterogeneity of chronic obstructive pulmonary disease (COPD). In addition to genetic analysis, the participants have been extensively characterized by clinical questionnaires, spirometry, volumetric inspiratory and expiratory computed tomography, and longitudinal follow-up, including follow-up computed tomography at 5 years after enrollment. The purpose of this state-of-the-art review is to summarize the major advances in our understanding of COPD resulting from the imaging findings in the COPDGene study. Imaging features that are associated with adverse clinical outcomes include early interstitial lung abnormalities, visual presence and pattern of emphysema, the ratio of pulmonary artery to ascending aortic diameter, quantitative evaluation of emphysema, airway wall thickness, and expiratory gas trapping. COPD is characterized by the early involvement of the small conducting airways, and the addition of expiratory scans has enabled measurement of small airway disease. Computational advances have enabled indirect measurement of nonemphysematous gas trapping. These metrics have provided insights into the pathogenesis and prognosis of COPD and have aided early identification of disease. Important quantifiable extrapulmonary findings include coronary artery calcification, cardiac morphology, intrathoracic and extrathoracic fat, and osteoporosis. Current active research includes identification of novel quantitative measures for emphysema and airway disease, evaluation of dose reduction techniques, and use of deep learning for phenotyping COPD.

Objective: To evaluate CT-ventilation imaging (CTVI) within a well-characterized, healthy cohort with no respiratory symptoms and examine the correlation between CTVI and concurrent pulmonary function test (PFT). Methods: CT scans and PFTs from 77 Caucasian participants in the NORM dataset (clinicaltrials.gov NCT00848406) were analyzed. CTVI was generated using the robust Integrated Jacobian Formulation (IJF) method. IJF estimated total lung capacity (TLC) was computed from CTVI. Bias-adjusted Pearson’s correlation between PFT and IJF-based TLC was computed. Results: IJF- and PFT-measured TLC showed a good correlation for both males and females [males: 0.657, 95% CI (0.438–0.797); females: 0.667, 95% CI (0.416–0.817)]. When adjusting for age, height, smoking, and abnormal CT scan, correlation moderated [males: 0.432, 95% CI (0.129–0.655); females: 0.540, 95% CI (0.207–0.753)]. Visual inspection of CTVI revealed participants who had functional defects, despite the fact that all participant had normal high-resolution CT scan. Conclusion: In this study, we demonstrate that IJF computed CTVI has good correlation with concurrent PFT in a well-validated patient cohort with no respiratory symptoms. Advances in knowledge: IJF-computed CTVI’s overall numerical robustness and consistency with PFT support its potential as a method for providing spatiotemporal assessment of high and low function areas on volumetric non-contrast CT scan.

Introduction: Impact of ultra-low-dose (ULD) computed tomography (CT) on quantification of structural disease and structure-function relationships in early Cystic Fibrosis (CF) lung disease have not been studied to date. Aim: To quantify structural lung disease and compare same session standard low radiation dose (LD) and ULD CT with pulmonary function measures in early CF lung disease. Methods: 46 CF subjects (age 11(6-17) yrs) with mild lung disease (FEV1≥70%pred) performed multiple breath washout (MBW), and spirometry directed paired inspiratory/expiratory CT with LD (CTDIvol: 1.23 mGy) and ULD (CTDIvol: 0.22 mGy). Quantification was performed automatically by validated institutional CT software. Results: Effective radiation dose was reduced by 78% in ULD vs. LD. Rates of abnormality were highest for CT and MBW and lowest for spirometry. Strong correlations were observed between LD and ULD readouts (gas trapping r=0.91, p

Bone is a composite biomaterial of mineral crystals, organic matrix, and water. Each contributes to bone quality and strength and may change independently, or together, with disease progression and treatment. Even so, there is a near ubiquitous reliance on ionizing x-ray-based approaches to measure bone mineral density (BMD) which is unable to fully characterize bone strength and may not adequately predict fracture risk. Characterization of treatment efficacy in bone diseases of altered remodeling is complicated by the lack of imaging modality able to safely monitor material-level and biochemical changes in vivo. To improve upon the current state of bone imaging, we tested the efficacy of Multi Band SWeep Imaging with Fourier Transformation (MB-SWIFT) magnetic resonance imaging (MRI) as a readout of bone derangement in an estrogen deficient ovariectomized (OVX) rat model during growth. MB-SWIFT MRI-derived BMD correlated significantly with BMD measured using micro-computed tomography (μCT). In this rodent model, growth appeared to overcome estrogen deficiency as bone mass continued to increase longitudinally over the duration of the study. Nonetheless, after 10 weeks of intervention, MB-SWIFT detected significant changes consistent with estrogen deficiency in cortical water, cortical matrix organization (T1), and marrow fat. Findings point to MB-SWIFT's ability to quantify BMD in good agreement with μCT while providing additive quantitative outcomes about bone quality in a manner consistent with estrogen deficiency. These results indicate MB-SWIFT as a non-ionizing imaging strategy with value for bone imaging and may be a promising technique to progress to the clinic for monitoring and clinical management of patients with bone diseases such as osteoporosis.

Despite good performance for medical image segmentation, deep convolutional neural networks (CNNs) have not been widely accepted in clinical practice as they are complex and tend to fail silently. Additionally, uncertainty in their predictions are not well understood, making them obscure and challenging to interpret. Automatically detecting possible failures in network predictions is important, as we can refer such cases for manual inspection or correction by human observers. In this paper, we analyse the uncertainty for deep CNN-based lung lobe segmentation in computed tomography (CT) scans by proposing a test-time augmentation-based aleatoric uncertainty measure. Through this analysis, we produce spatial uncertainty maps, from which a clinician can observe where and why a system thinks it is failing, and quantify the image-level prediction of failure. Our results show that such an uncertainty measure is highly correlated to segmentation accuracy and therefore presents an inherent measure of segmentation quality.

Background The observation that patients with idiopathic pulmonary fibrosis (IPF) can have higher than normal expiratory flow rates at low lung volumes led to the conclusion that the airways are spared in IPF. This study aimed to re-examine the hypothesis that airways are spared in IPF using a multiresolution imaging protocol that combines multidetector CT (MDCT), with micro-CT and histology. Methods This was a retrospective cohort study comparing explanted lungs from patients with severe IPF treated by lung transplantation with a cohort of unused donor (control) lungs. The donor control lungs had no known lung disease, comorbidities, or structural lung injury, and were deemed appropriate for transplantation on review of the clinical files. The diagnosis of IPF in the lungs from patients was established by a multidisciplinary consensus committee according to existing guidelines, and was confirmed by video-assisted thoracic surgical biopsy or by pathological examination of the contralateral lung. The control and IPF groups were matched for age, sex, height, and bodyweight. Samples of lung tissue were compared using the multiresolution imaging approach: a cascade of clinical MDCT, micro-CT, and histological imaging. We did two experiments: in experiment 1, all the lungs were randomly sampled; in experiment 2, samples were selected from regions of minimal and established fibrosis. The patients and donors were recruited from the Katholieke Universiteit Leuven (Leuven, Belgium) and the University of Pennsylvania Hospital (Philadelphia, PA, USA). The study took place at the Katholieke Universiteit Leuven, and the University of British Columbia (Vancouver, BC, Canada). Findings Between Oct 5, 2009, and July 22, 2016, explanted lungs from patients with severe IPF (n=11), were compared with a cohort of unused donor (control) lungs (n=10), providing 240 samples of lung tissue for comparison using the multiresolution imaging approach. The MDCT specimen scans show that the number of visible airways located between the ninth generation (control 69 [SD 22] versus patients with IPF 105 [33], p=0.0023) and 14th generation (control 9 [6] versus patients with IPF 49 [28], p

Contains fulltext : 220761.pdf (Publisher’s version ) (Open Access) Rationale: The decades-long progression of chronic obstructive pulmonary disease (COPD) renders identifying different trajectories of disease progression challenging.Objectives: To identify subtypes of patients with COPD with distinct longitudinal progression patterns using a novel machine-learning tool called "Subtype and Stage Inference" (SuStaIn) and to evaluate the utility of SuStaIn for patient stratification in COPD.Methods: We applied SuStaIn to cross-sectional computed tomography imaging markers in 3,698 Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1-4 patients and 3,479 controls from the COPDGene (COPD Genetic Epidemiology) study to identify subtypes of patients with COPD. We confirmed the identified subtypes and progression patterns using ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) data. We assessed the utility of SuStaIn for patient stratification by comparing SuStaIn subtypes and stages at baseline with longitudinal follow-up data.Measurements and Main Results: We identified two trajectories of disease progression in COPD: a "Tissue-->Airway" subtype (n = 2,354, 70.4%), in which small airway dysfunction and emphysema precede large airway wall abnormalities, and an "Airway-->Tissue" subtype (n = 988, 29.6%), in which large airway wall abnormalities precede emphysema and small airway dysfunction. Subtypes were reproducible in ECLIPSE. Baseline stage in both subtypes correlated with future FEV1/FVC decline (r = -0.16 [P < 0.001] in the Tissue-->Airway group; r = -0.14 [P = 0.011] in the Airway-->Tissue group). SuStaIn placed 30% of smokers with normal lung function at elevated stages, suggesting imaging changes consistent with early COPD. Individuals with early changes were 2.5 times more likely to meet COPD diagnostic criteria at follow-up.Conclusions: We demonstrate two distinct patterns of disease progression in COPD using SuStaIn, likely representing different endotypes. One third of healthy smokers have detectable imaging changes, suggesting a new biomarker of "early COPD."

Abstract Impaired single breath carbon monoxide diffusing capacity (DLCO) is associated with emphysema. Small airways disease (SAD) may be a precursor lesion to emphysema, but the relationship between SAD and DLCO is undescribed. We hypothesized that in mild COPD, functional SAD (fSAD) defined by computed tomography (CT) and Parametric Response Mapping methodology would correlate with impaired DLCO. Using data from ever-smokers in the COPDGene cohort, we established that fSAD correlated significantly with lower DLCO among both non-obstructed and GOLD 1–2 subjects. The relationship between DLCO with CT-defined emphysema was present in all GOLD stages, but most prominent in severe disease. Trial registration NCT00608764. Registry: COPDGene. Registered 06 February 2008, retrospectively registered.