Topologic Parametric Response Mapping Identifies Tissue Subtypes Associated with Emphysema Progression

RATIONALE AND OBJECTIVES

Small airways disease (SAD) and emphysema are significant components of chronic obstructive pulmonary disease (COPD), a heterogenous disease where predicting progression is difficult. SAD, a principal cause of airflow obstruction in mild COPD, has been identified as a precursor to emphysema. Parametric Response Mapping (PRM) of chest computed tomography (CT) can help distinguish SAD from emphysema. Specifically, topologic PRM can define local patterns of both diseases to characterize how and in whom COPD progresses. We aimed to determine if distribution of CT-based PRM of functional SAD (fSAD) is associated with emphysema progression.

MATERIALS AND METHODS

We analyzed paired inspiratory-expiratory chest CT scans at baseline and 5-year follow up in 1495 COPDGene subjects using topological analyses of PRM classifications. By spatially aligning temporal scans, we mapped local emphysema at year five to baseline lobar PRM-derived topological readouts. K-means clustering was applied to all observations. Subjects were subtyped based on predominant PRM cluster assignments and assessed using non-parametric statistical tests to determine differences in PRM values, pulmonary function metrics, and clinical measures.

RESULTS

We identified distinct lobar imaging patterns and classified subjects into three radiologic subtypes: emphysema-dominant (ED), fSAD-dominant (FD), and fSAD-transition (FT: transition from healthy lung to fSAD). Relative to year five emphysema, FT showed rapid local emphysema progression (-57.5% ± 1.1) compared to FD (-49.9% ± 0.5) and ED (-33.1% ± 0.4). FT consisted primarily of at-risk subjects (roughly 60%) with normal spirometry.

CONCLUSION

The FT subtype of COPD may allow earlier identification of individuals without spirometrically-defined COPD at-risk for developing emphysema.

Local heterogeneity of normal lung parenchyma and small airways disease are associated with COPD severity and progression

BACKGROUND

Small airways disease (SAD) is a major cause of airflow obstruction in COPD patients and has been identified as a precursor to emphysema. Although the amount of SAD in the lungs can be quantified using our Parametric Response Mapping (PRM) approach, the full breadth of this readout as a measure of emphysema and COPD progression has yet to be explored. We evaluated topological features of PRM-derived normal parenchyma and SAD as surrogates of emphysema and predictors of spirometric decline.

METHODS

PRM metrics of normal lung (PRMNorm) and functional SAD (PRMfSAD) were generated from CT scans collected as part of the COPDGene study (n = 8956). Volume density (V) and Euler-Poincaré Characteristic (χ) image maps, measures of the extent and coalescence of pocket formations (i.e., topologies), respectively, were determined for both PRMNorm and PRMfSAD. Association with COPD severity, emphysema, and spirometric measures were assessed via multivariable regression models. Readouts were evaluated as inputs for predicting FEV1 decline using a machine learning model.

RESULTS

Multivariable cross-sectional analysis of COPD subjects showed that V and χ measures for PRMfSAD and PRMNorm were independently associated with the amount of emphysema. Readouts χfSAD (β of 0.106, p < 0.001) and VfSAD (β of 0.065, p = 0.004) were also independently associated with FEV1% predicted. The machine learning model using PRM topologies as inputs predicted FEV1 decline over five years with an AUC of 0.69.

CONCLUSIONS

We demonstrated that V and χ of fSAD and Norm have independent value when associated with lung function and emphysema. In addition, we demonstrated that these readouts are predictive of spirometric decline when used as inputs in a ML model. Our topological PRM approach using PRMfSAD and PRMNorm may show promise as an early indicator of emphysema onset and COPD progression.

Quantitative CT of Normal Lung Parenchyma and Small Airways Disease Topologies are Associated With COPD Severity and Progression

Objectives

Small airways disease (SAD) is a major cause of airflow obstruction in COPD patients, and has been identified as a precursor to emphysema. Although the amount of SAD in the lungs can be quantified using our Parametric Response Mapping (PRM) approach, the full breadth of this readout as a measure of emphysema and COPD progression has yet to be explored. We evaluated topological features of PRM-derived normal parenchyma and SAD as surrogates of emphysema and predictors of spirometric decline.

Materials and Methods

PRM metrics of normal lung (PRMNorm) and functional SAD (PRMfSAD) were generated from CT scans collected as part of the COPDGene study (n=8956). Volume density (V) and Euler-Poincaré Characteristic (χ) image maps, measures of the extent and coalescence of pocket formations (i.e., topologies), respectively, were determined for both PRMNorm and PRMfSAD. Association with COPD severity, emphysema, and spirometric measures were assessed via multivariable regression models. Readouts were evaluated as inputs for predicting FEV1 decline using a machine learning model.

Results

Multivariable cross-sectional analysis of COPD subjects showed that V and χ measures for PRMfSAD and PRMNorm were independently associated with the amount of emphysema. Readouts χfSAD (β of 0.106, p<0.001) and VfSAD (β of 0.065, p=0.004) were also independently associated with FEV1% predicted. The machine learning model using PRM topologies as inputs predicted FEV1 decline over five years with an AUC of 0.69.

Conclusions

We demonstrated that V and χ of fSAD and Norm have independent value when associated with lung function and emphysema. In addition, we demonstrated that these readouts are predictive of spirometric decline when used as inputs in a ML model. Our topological PRM approach using PRMfSAD and PRMNorm may show promise as an early indicator of emphysema onset and COPD progression.

Parametric Response Mapping of FLAIR MRI Provides an Early Indication of Progression Risk in Glioblastoma

RATIONALE AND OBJECTIVES

Glioblastoma image evaluation utilizes Magnetic Resonance Imaging contrast-enhanced, T1-weighted, and noncontrast T2-weighted fluid-attenuated inversion recovery (FLAIR) acquisitions. Disease progression assessment relies on changes in tumor diameter, which correlate poorly with survival. To improve treatment monitoring in glioblastoma, we investigated serial voxel-wise comparison of anatomically-aligned FLAIR signal as an early predictor of GBM progression.

MATERIALS AND METHODS

We analyzed longitudinal normalized FLAIR images (rFLAIR) from 52 subjects using voxel-wise Parametric Response Mapping (PRM) to monitor volume fractions of increased (PRM_rFLAIR+), decreased (PRM_rFLAIR-), or unchanged (PRM_rFLAIR0) rFLAIR intensity. We determined response by rFLAIR between pretreatment and 10 weeks posttreatment. Risk of disease progression in a subset of subjects (N = 26) with stable disease or partial response as defined by Response Assessment in Neuro-Oncology (RANO) criteria was assessed by PRM_rFLAIR between weeks 10 and 20 and continuously until the PRM_rFLAIR+ exceeded a defined threshold. RANO defined criteria were compared with PRM-derived outcomes for tumor progression detection.

RESULTS

Patient stratification for progression-free survival (PFS) and overall survival (OS) was achieved at week 10 using RANO criteria (PFS: p <0.0001; OS: p <0.0001), relative change in FLAIR-hyperintense volume (PFS: p = 0.0011; OS: p <0.0001), and PRM_rFLAIR+ (PFS: p <0.01; OS: p <0.001). PRM_rFLAIR+ also stratified responding patients' progression between weeks 10 and 20 (PFS: p <0.05; OS: p = 0.01) while changes in FLAIR-volume measurements were not predictive. As a continuous evaluation, PRM_rFLAIR+ exceeding 10% stratified patients for PFA after 5.6 months (p<0.0001), while RANO criteria did not stratify patients until 15.4 months (p <0.0001).

CONCLUSION

PRM_rFLAIR may provide an early biomarker of disease progression in glioblastoma.

Improved detection of air trapping on expiratory computed tomography using deep learning

BACKGROUND

Radiologic evidence of air trapping (AT) on expiratory computed tomography (CT) scans is associated with early pulmonary dysfunction in patients with cystic fibrosis (CF). However, standard techniques for quantitative assessment of AT are highly variable, resulting in limited efficacy for monitoring disease progression.

OBJECTIVE

To investigate the effectiveness of a convolutional neural network (CNN) model for quantifying and monitoring AT, and to compare it with other quantitative AT measures obtained from threshold-based techniques.

MATERIALS AND METHODS

Paired volumetric whole lung inspiratory and expiratory CT scans were obtained at four time points (0, 3, 12 and 24 months) on 36 subjects with mild CF lung disease. A densely connected CNN (DN) was trained using AT segmentation maps generated from a personalized threshold-based method (PTM). Quantitative AT (QAT) values, presented as the relative volume of AT over the lungs, from the DN approach were compared to QAT values from the PTM method. Radiographic assessment, spirometric measures, and clinical scores were correlated to the DN QAT values using a linear mixed effects model.

RESULTS

QAT values from the DN were found to increase from 8.65% ± 1.38% to 21.38% ± 1.82%, respectively, over a two-year period. Comparison of CNN model results to intensity-based measures demonstrated a systematic drop in the Dice coefficient over time (decreased from 0.86 ± 0.03 to 0.45 ± 0.04). The trends observed in DN QAT values were consistent with clinical scores for AT, bronchiectasis, and mucus plugging. In addition, the DN approach was found to be less susceptible to variations in expiratory deflation levels than the threshold-based approach.

CONCLUSION

The CNN model effectively delineated AT on expiratory CT scans, which provides an automated and objective approach for assessing and monitoring AT in CF patients.

Influence of Inspiratory/Expiratory CT Registration on Quantitative Air Trapping

RATIONALE AND OBJECTIVES

The aim of this study was to assess variability in quantitative air trapping (QAT) measurements derived from spatially aligned expiration CT scans.

MATERIALS AND METHODS

Sixty-four paired CT examinations, from 16 school-age cystic fibrosis subjects examined at four separate time intervals, were used in this study. For each pair, visually inspected lobe segmentation maps were generated and expiration CT data were registered to the inspiration CT frame. Measurements of QAT, the percentage of voxels on the expiration CT scan below a set threshold were calculated for each lobe and whole-lung from the registered expiration CT and compared to the true values from the unregistered data.

RESULTS

A mathematical model, which simulates the effect of variable regions of lung deformation on QAT values calculated from aligned to those from unaligned data, showed the potential for large bias. Assessment of experimental QAT measurements using Bland-Altman plots corroborated the model simulations, demonstrating biases greater than 5% when QAT was approximately 40% of lung volume. These biases were removed when calculating QAT from aligned expiration CT data using the determinant of the Jacobian matrix. We found, by Dice coefficient analysis, good agreement between aligned expiration and inspiration segmentation maps for the whole-lung and all but one lobe (Dice coefficient > 0.9), with only the lingula generating a value below 0.9 (mean and standard deviation of 0.85 ± 0.06).

CONCLUSION

The subtle and predictable variability in corrected QAT observed in this study suggests that image registration is reliable in preserving the accuracy of the quantitative metrics.

Multimodal imaging provides insight into targeted therapy response in metastatic prostate cancer to the bone

Metastatic prostate cancer to bone remains incurable, driving efforts to develop individualized, targeted therapies to improve clinical outcomes while limiting adverse side-effects. Due to the complexity in cellular signaling pathways and the interaction between cancer and its microenvironment, multiparametric imaging approaches for treatment response may improve understanding of the biological effects of therapy. An orthotopic model of castration resistant prostate cancer (CRPC) bone metastasis was treated with the tyrosine kinase inhibitor Cabozantinib (CABO). Response was assessed using CT to monitor bone volumes, ^99mTc-MDP SPECT for bone metabolism, and anatomical and diffusion MRI for tumor volume and cell death. A concurrent clinical trial of CABO for CRPC patients also evaluated multimodality imaging in correlation with standard response criteria. Response in the preclinical study found significant slowing in tumor growth rate (P<0.01), rise in tumor apparent diffusion coefficient (ADC, P<0.001), and drop in ^99mTc-MDP adsorption (P<0.05). Loss of bone volume did not slow with treatment, attributed to the highly aggressive and osteolytic nature of the PC3 cell line. Clinical trial analysis found only a single subject who progressed after 12 weeks of therapy. Imaging at 6 weeks corroborated the 12-week radiological assessment with positive response visible as increased ADC and decreased vascular metrics. Conversely, the subject who progressed at 12 weeks had no change in ADC, and substantial drops in vascular metrics. These results showcase a multifaceted translational imaging approach for detecting targeted treatment response with effective blockade of tumor vascularization, tumor cell kill, and reduced proliferation.

Vascular Deformation Mapping (VDM) of Thoracic Aortic Enlargement in Aneurysmal Disease and Dissection

Thoracic aortic aneurysm is a common and lethal disease that requires regular imaging surveillance to determine timing of surgical repair and prevent major complications such as rupture. Current cross-sectional imaging surveillance techniques, largely based on computed tomography angiography, are focused on measurement of maximal aortic diameter, although this approach is limited to fixed anatomic positions and is prone to significant measurement error. Here we present preliminary results showing the feasibility of a novel technique for assessing change in aortic dimensions, termed vascular deformation mapping (VDM). This technique allows quantification of 3-dimensional changes in the aortic wall geometry through nonrigid coregistration of computed tomography angiography images and spatial Jacobian analysis of aortic deformation. Through several illustrative cases we demonstrate that this method can be used to measure changes in the aortic wall geometry among patients with stable and enlarging thoracic aortic aneurysm and dissection. Furthermore, VDM results yield observations about the presence, distribution, and rate of aortic wall deformation that are not apparent by routine clinical evaluation. Finally, we show the feasibility of superposing patient-specific VDM results on a 3-dimensional aortic model using color 3D printing and discuss future directions and potential applications for the VDM technique.

CT-Based Local Distribution Metric Improves Characterization of COPD

Parametric response mapping (PRM) of paired CT lung images has been shown to improve the phenotyping of COPD by allowing for the visualization and quantification of non-emphysematous air trapping component, referred to as functional small airways disease (fSAD). Although promising, large variability in the standard method for analyzing PRMfSAD has been observed. We postulate that representing the 3D PRMfSAD data as a single scalar quantity (relative volume of PRMfSAD) oversimplifies the original 3D data, limiting its potential to detect the subtle progression of COPD as well as varying subtypes. In this study, we propose a new approach to analyze PRM. Based on topological techniques, we generate 3D maps of local topological features from 3D PRMfSAD classification maps. We found that the surface area of fSAD (SfSAD) was the most robust and significant independent indicator of clinically meaningful measures of COPD. We also confirmed by micro-CT of human lung specimens that structural differences are associated with unique SfSAD patterns, and demonstrated longitudinal feature alterations occurred with worsening pulmonary function independent of an increase in disease extent. These findings suggest that our technique captures additional COPD characteristics, which may provide important opportunities for improved diagnosis of COPD patients.

Semiautomated Workflow for Clinically Streamlined Glioma Parametric Response Mapping

Management of glioblastoma multiforme remains a challenging problem despite recent advances in targeted therapies. Timely assessment of therapeutic agents is hindered by the lack of standard quantitative imaging protocols for determining targeted response. Clinical response assessment for brain tumors is determined by volumetric changes assessed at 10 weeks post-treatment initiation. Further, current clinical criteria fail to use advanced quantitative imaging approaches, such as diffusion and perfusion magnetic resonance imaging. Development of the parametric response mapping (PRM) applied to diffusion-weighted magnetic resonance imaging has provided a sensitive and early biomarker of successful cytotoxic therapy in brain tumors while maintaining a spatial context within the tumor. Although PRM provides an earlier readout than volumetry and sometimes greater sensitivity compared with traditional whole-tumor diffusion statistics, it is not routinely used for patient management; an automated and standardized software for performing the analysis and for the generation of a clinical report document is required for this. We present a semiautomated and seamless workflow for image coregistration, segmentation, and PRM classification of glioblastoma multiforme diffusion-weighted magnetic resonance imaging scans. The software solution can be integrated using local hardware or performed remotely in the cloud while providing connectivity to existing picture archive and communication systems. This is an important step toward implementing PRM analysis of solid tumors in routine clinical practice.

A Pilot Study of Quantitative MRI Parametric Response Mapping of Bone Marrow Fat for Treatment Assessment in Myelofibrosis

Myelofibrosis (MF) is a hematologic neoplasm arising as a primary disease or secondary to other myeloproliferative neoplasms (MPNs). Both primary and secondary MF are uniquely associated with progressive bone marrow fibrosis, displacing normal hematopoietic cells from the marrow space and disrupting normal production of mature blood cells. Activation of the JAK2 signaling pathway in hematopoietic stem cells commonly causes MF, and ruxolitinib, a drug targeting this pathway, is the treatment of choice for many patients. However, current measures of disease status in MF do not necessarily predict response to treatment with ruxolitinib or other drugs in MF. Bone marrow biopsies are invasive and prone to sampling error, while measurements of spleen volume only indirectly reflect bone marrow status. Toward the goal of developing an imaging biomarker for treatment response in MF, we present preliminary results from a prospective clinical study evaluating parametric response mapping (PRM) of quantitative Dixon MRI bone marrow fat fraction maps in four MF patients treated with ruxolitinib. PRM allows for the voxel-wise identification of significant change in quantitative imaging readouts over time, in this case the bone marrow fat content. We identified heterogeneous response patterns of bone marrow fat among patients and within different bone marrow sites in the same patient. We also observed discordance between changes in bone marrow fat fraction and reductions in spleen volume, the standard imaging metric for treatment efficacy. This study provides initial support for PRM analysis of quantitative MRI of bone marrow fat to monitor response to therapy in MF, setting the stage for larger studies to further develop and validate this method as a complementary imaging biomarker for this disease.

Potential for Early Fracture Risk Assessment in Patients with Metastatic Bone Disease using Parametric Response Mapping of CT Images

Pathologic vertebral compression fractures (PVCFs) cause significant morbidity in patients with metastatic bone disease. Limitations in existing clinical biomarkers leave clinicians without reliable metrics for predicting PVCF, thus impeding efforts to prevent this severe complication. To establish the feasibility of a new method for defining the risk of a PVCF, we retrospectively analyzed serial computed tomography (CT) scans from 5 breast cancer patients using parametric response mapping (PRM) to quantify dynamic bone miniral density (BMD) changes that preceded an event. Vertebrae segmented from each scan were registered to the same spatial frame and voxel classification was accomplished using a predetermined threshold of change in Hounsfield units (HU), resulting in relative volumes of increased (PRM_HU+), decreased (PRM_HU−), or unchanged (PRM_HU0) attenuation. A total of 7 PVCFs were compared to undiseased vertebrae in each patient serving as controls. A receiver operator curve (ROC) analysis identified optimal imaging times for group stratification. BMD changes were apparent by an elevated PRM_HU+ as early as 1 year before fracture. ROC analysis showed poor performance of PRM_HU− in stratifying PVCFs versus controls. As early as 6 months before PVCF, PRM_HU+ was significantly larger (12.9 ± 11.6%) than control vertebrae (2.3 ± 2.5%), with an area under the curve of 0.918 from an ROC analysis. Mean HU changes were also significant between PVCF (26.8 ± 26.9%) and control (−2.2 ± 22.0%) over the same period. A PRM analysis of BMD changes using standard CT imaging was sensitive for spatially resolving changes that preceded structural failure in these patients.

Apparent diffusion coefficient is highly reproducible on preclinical imaging systems: Evidence from a seven-center multivendor study

PURPOSE

To evaluate between-site agreement of apparent diffusion coefficient (ADC) measurements in preclinical magnetic resonance imaging (MRI) systems.

MATERIALS AND METHODS

A miniaturized thermally stable ice-water phantom was devised. ADC (mean and interquartile range) was measured over several days, on 4.7T, 7T, and 9.4T Bruker, Agilent, and Magnex small-animal MRI systems using a common protocol across seven sites. Day-to-day repeatability was expressed as percent variation of mean ADC between acquisitions. Cross-site reproducibility was expressed as 1.96 × standard deviation of percent deviation of ADC values.

RESULTS

ADC measurements were equivalent across all seven sites with a cross-site ADC reproducibility of 6.3%. Mean day-to-day repeatability of ADC measurements was 2.3%, and no site was identified as presenting different measurements than others (analysis of variance [ANOVA] P = 0.02, post-hoc test n.s.). Between-slice ADC variability was negligible and similar between sites (P = 0.15). Mean within-region-of-interest ADC variability was 5.5%, with one site presenting a significantly greater variation than the others (P = 0.0013).

CONCLUSION

Absolute ADC values in preclinical studies are comparable between sites and equipment, provided standardized protocols are employed.

Development of a Multiparametric Voxel-Based Magnetic Resonance Imaging Biomarker for Early Cancer Therapeutic Response Assessment

Quantitative magnetic resonance imaging (MRI)-based biomarkers, which capture physiological and functional tumor processes, were evaluated as imaging surrogates of early tumor response following chemoradiotherapy in glioma patients. A multiparametric extension of a voxel-based analysis, referred as the parametric response map (PRM), was applied to quantitative MRI maps to test the predictive potential of this metric for detecting response. Fifty-six subjects with newly diagnosed high-grade gliomas treated with radiation and concurrent temozolomide were enrolled in a single-site prospective institutional review board-approved MRI study. Apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps were acquired before therapy and 3 weeks after therapy was initiated. Multiparametric PRM (mPRM) was applied to both physiological MRI maps and evaluated as an imaging biomarker of patient survival. For comparison, single-biomarker PRMs were also evaluated in this study. The simultaneous analysis of ADC and rCBV by the mPRM approach was found to improve the predictive potential for patient survival over single PRM measures. With an array of quantitative imaging parameters being evaluated as biomarkers of therapeutic response, mPRM shows promise as a new methodology for consolidating physiologically distinct imaging parameters into a single interpretable and quantitative metric.

The Impact of Sources of Variability on Parametric Response Mapping of Lung CT Scans

Parametric response mapping (PRM) of inspiration and expiration computed tomography (CT) images improves the radiological phenotyping of chronic obstructive pulmonary disease (COPD). PRM classifies individual voxels of lung parenchyma as normal, emphysematous, or nonemphysematous air trapping. In this study, bias and noise characteristics of the PRM methodology to CT and clinical procedures were evaluated to determine best practices for this quantitative technique. Twenty patients of varying COPD status with paired volumetric inspiration and expiration CT scans of the lungs were identified from the baseline COPDGene cohort. The impact of CT scanner manufacturer and reconstruction kernels were evaluated as potential sources of variability in PRM measurements along with simulations to quantify the impact of inspiration/expiration lung volume levels, misregistration, and image spacing on PRM measurements. Negligible variation in PRM metrics was observed when CT scanner type and reconstruction were consistent and inspiration/expiration lung volume levels were near target volumes. CT scanner Hounsfield unit drift occurred but remained difficult to ameliorate. Increasing levels of image misregistration and CT slice spacing were found to have a minor effect on PRM measurements. PRM-derived values were found to be most sensitive to lung volume levels and mismatched reconstruction kernels. As with other quantitative imaging techniques, reliable PRM measurements are attainable when consistent clinical and CT protocols are implemented.

Feasibility analysis of the parametric response map as an early predictor of treatment efficacy in head and neck cancer

BACKGROUND AND PURPOSE

Estimating changes in the volume transfer constant, normalized area under the contrast-enhancement time curve at 60 seconds, and fractional blood plasma volume by using dynamic contrast-enhanced MR imaging may be useful in predicting tumor response to chemoradiation. We hypothesized that the parametric response map, a voxel-by-voxel analysis of quantitative dynamic contrast-enhanced MR imaging maps, predicts survival in patients with head and neck cancer.

MATERIALS AND METHODS

Ten patients with locoregionally advanced head and neck squamous cell carcinoma underwent definitive concurrent chemoradiation therapy. For each patient, dynamic contrast-enhanced MR imaging data were collected before and 2 weeks after treatment initiation. Change in perfusion parameters within the primary tumor volume with time was analyzed by parametric response mapping and by whole-tumor mean percentage change. Outcome was defined as overall survival. The perfusion parameter and metric most predictive of outcome were identified. Overall survival was estimated by the log-rank test and Kaplan-Meier survival curve.

RESULTS

The volume transfer constant and normalized area under the contrast-enhancement time curve at 60 seconds were predictive of survival both in parametric response map analysis (volume transfer constant, P = .002; normalized area under the contrast-enhancement time curve at 60 seconds, P = .02) and in the percentage change analysis (volume transfer constant, P = .04; normalized area under the contrast-enhancement time curve at 60 seconds, P = .02). Blood plasma volume predicted survival in neither analysis.

CONCLUSIONS

Parametric response mapping of MR perfusion biomarkers could potentially guide treatment modification in patients with predicted treatment failure. Larger studies are needed to determine whether parametric response map analysis or percentage signal change in these perfusion parameters is the stronger predictor of survival.

Parametric response mapping monitors temporal changes on lung CT scans in the subpopulations and intermediate outcome measures in COPD Study (SPIROMICS)

RATIONALE AND OBJECTIVES

The longitudinal relationship between regional air trapping and emphysema remains unexplored. We have sought to demonstrate the utility of parametric response mapping (PRM), a computed tomography (CT)-based biomarker, for monitoring regional disease progression in chronic obstructive pulmonary disease (COPD) patients, linking expiratory- and inspiratory-based CT metrics over time.

MATERIALS AND METHODS

Inspiratory and expiratory lung CT scans were acquired from 89 COPD subjects with varying Global Initiative for Chronic Obstructive Lung Disease (GOLD) status at 30 days (n = 13) or 1 year (n = 76) from baseline as part of the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) clinical trial. PRMs of CT data were used to quantify the relative volumes of normal parenchyma (PRM(Normal)), emphysema (PRM(Emph)), and functional small airways disease (PRM(fSAD)). PRM measurement variability was assessed using the 30-day interval data. Changes in PRM metrics over a 1-year period were correlated to pulmonary function (forced expiratory volume at 1 second [FEV1]). A theoretical model that simulates PRM changes from COPD was compared to experimental findings.

RESULTS

PRM metrics varied by ∼6.5% of total lung volume for PRM(Normal) and PRM(fSAD) and 1% for PRM(Emph) when testing 30-day repeatability. Over a 1-year interval, only PRM(Emph) in severe COPD subjects produced significant change (19%-21%). However, 11 of 76 subjects showed changes in PRM(fSAD) greater than variations observed from analysis of 30-day data. Mathematical model simulations agreed with experimental PRM results, suggesting fSAD is a transitional phase from normal parenchyma to emphysema.

CONCLUSIONS

PRM of lung CT scans in COPD patients provides an opportunity to more precisely characterize underlying disease phenotypes, with the potential to monitor disease status and therapy response.

Phosphorylation of FADD by the kinase CK1α promotes KRASG12D-induced lung cancer

Genomic amplification of the gene encoding and phosphorylation of the protein FADD (Fas-associated death domain) is associated with poor clinical outcome in lung cancer and in head and neck cancer. Activating mutations in the guanosine triphosphatase RAS promotes cell proliferation in various cancers. Increased abundance of phosphorylated FADD in patient-derived tumor samples predicts poor clinical outcome. Using immunohistochemistry analysis and in vivo imaging of conditional mouse models of KRAS(G12D)-driven lung cancer, we found that the deletion of the gene encoding FADD suppressed tumor growth, reduced the proliferative index of cells, and decreased the activation of downstream effectors of the RAS-MAPK (mitogen-activated protein kinase) pathway that promote the cell cycle, including retinoblastoma (RB) and cyclin D1. In mouse embryonic fibroblasts, the induction of mitosis upon activation of KRAS required FADD and the phosphorylation of FADD by CK1α (casein kinase 1α). Deleting the gene encoding CK1α in KRAS mutant mice abrogated the phosphorylation of FADD and suppressed lung cancer development. Phosphorylated FADD was most abundant during the G2/M phase of the cell cycle, and mass spectrometry revealed that phosphorylated FADD interacted with kinases that mediate the G2/M transition, including PLK1 (Polo-like kinase 1), AURKA (Aurora kinase A), and BUB1 (budding uninhibited by benzimidazoles 1). This interaction was decreased in cells treated with a CKI-7, a CK1α inhibitor. Therefore, as the kinase that phosphorylates FADD downstream of RAS, CK1α may be a therapeutic target for KRAS-driven lung cancer.

Abstract 106: A requirement for FADD and its phosphorylation for KRAS-driven oncogenesis

Lung cancer accounts for 27% of all cancer deaths worldwide. 80% of these deaths are due to a specific subtype Non-small cell lung cancer (NSCLC). Almost half of all NSCLC patients carry gatekeeper mutations in the EGFR/KRAS pathway. Although KRAS mutations are the most prevalent mutations in human cancers, therapies targeting KRAS have fallen short. Tyrosine kinase inhibitors have been successful in NSCLC patients with mutant or amplified EGFR, however resistance to these inhibitors is common. Thus therapies targeting mutant KRAS or its downstream effectors are desperately needed for the treatment of NSCLC.

FAS Associated Death Domain (FADD) is a well characterized adaptor protein involved in death receptor mediated apoptosis, but more recently has been implicated in the regulation of other cellular functions such as cell cycle and proliferation. Increasing evidence suggests that it is FADD's phosphorylated state which regulates these non-apoptotic signaling pathways. We and others have previously identified phosphorylated FADD as a predictor of aggressiveness and clinical stage in lung and head and neck cancer patients, respectively.

Using non-invasive bioluminescence and µCT imaging in a Kras driven mouse model of NSCLC, we demonstrate the requirement for FADD in tumor progression. Lung-specific activation of KrasG12D and simultaneous FADD deletion resulted in reduced lung tumor burden. Furthermore lung lesions of KrasG12D FADD null mice were significantly smaller with a decrease in proliferative index. Similar findings were obtained in MEFs, where siRNA mediated Kras knockdown or the use of MEK inhibitors resulted in a Kras dependent decrease in FADD phosphorylation, decrease in cell cycle progression and cell proliferation. These data propound the phosphorylation of FADD as a downstream event of Kras signaling and demonstrate its requirement for Kras dependent neoplasia in a mouse model for NSCLC.

In summary our findings demonstrate that elevated FADD and phosphorylated FADD levels are predictive of poor survival in an animal model of NSCLC agreeing with clinical findings. Furthermore, it implicates phosphorylation of FADD downstream of KRAS activation and thus suggests FADD phosphorylation as a valid target in the treatment of NSCLC patients.

Citation Format: Brittany M. Bowman, Stefanie Galban, Benjamin A. Hoff, Kevin A. Heist, Jennifer L. Boes, Craig J. Galban, Rajiv M. Patel, Jianke Zhang, Brian D. Ross, Alnawaz Rehemtulla. A requirement for FADD and its phosphorylation for KRAS-driven oncogenesis. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 106. doi:10.1158/1538-7445.AM2014-106

Parametric response mapping of CT images provides early detection of local bone loss in a rat model of osteoporosis

Loss of bone mass due to disease, such as osteoporosis and metastatic cancer to the bone, is a leading cause of orthopedic complications and hospitalization. Onset of bone loss resulting from disease increases the risk of incurring fractures and subsequent pain, increasing medical expenses while reducing quality of life. Although current standard CT-based protocols provide adequate prognostic information for assessing bone loss, many of the techniques for evaluating CT scans rely on measures based on whole-bone summary statistics. This reduces the sensitivity at identifying local regions of bone resorption, as well as formation. In this study, we evaluate the effectiveness of a voxel-based image post-processing technique, called the Parametric Response Map (PRM), for identifying local changes in bone mass in weight-bearing bones on CT scans using an established animal model of osteoporosis. Serial CT scans were evaluated weekly using PRM subsequent to ovariectomy or sham surgeries over the period of one month. For comparison, bone volume fraction and mineral density measurements were acquired and found to significantly differ between groups starting 3 weeks post-surgery. High resolution ex vivo measurements acquired four weeks post-surgery validated the extent of bone loss in the surgical groups. In contrast to standard methodologies for assessing bone loss, PRM results were capable of identifying local decreases in bone mineral by week 2, which were found to be significant between groups. This study concludes that PRM is able to detect changes in bone mineral with higher sensitivity and spatial differentiation than conventional techniques for evaluating CT scans, which may aid in clinical decision making for patients suffering from bone loss.

DCE and DW-MRI monitoring of vascular disruption following VEGF-Trap treatment of a rat glioma model

Vascular-targeted therapies have shown promise as adjuvant cancer treatment. As these agents undergo clinical evaluation, sensitive imaging biomarkers are needed to assess drug target interaction and treatment response. In this study, dynamic contrast enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI) were evaluated for detecting response of intracerebral 9 L gliosarcomas to the antivascular agent VEGF-Trap, a fusion protein designed to bind all forms of Vascular Endothelial Growth Factor-A (VEGF-A) and Placental Growth Factor (PGF). Rats with 9 L tumors were treated twice weekly for two weeks with vehicle or VEGF-Trap. DCE- and DW-MRI were performed one day prior to treatment initiation and one day following each administered dose. Kinetic parameters (K(trans), volume transfer constant; k(ep), efflux rate constant from extravascular/extracellular space to plasma; and v(p), blood plasma volume fraction) and the apparent diffusion coefficient (ADC) over the tumor volumes were compared between groups. A significant decrease in kinetic parameters was observed 24 hours following the first dose of VEGF-Trap in treated versus control animals (p < 0.05) and was accompanied by a decline in ADC values. In addition to the significant hemodynamic effect, VEGF-Trap treated animals exhibited significantly longer tumor doubling times (p < 0.05) compared to the controls. Histological findings were found to support imaging response metrics. In conclusion, kinetic MRI parameters and change in ADC have been found to serve as sensitive and early biomarkers of VEGF-Trap anti-vascular targeted therapy.

Abstract 2434: A genetically engineered mouse for imaging of apoptosis in a tissue specific manner

The importance of the apoptotic machinery is exemplified in a number of disease processes. For example, inhibition of apoptosis can result in a number of cancers, autoimmune diseases, inflammatory diseases, and viral infections. Cancer is characterized by dysregulated cell proliferation and altered cell death, which constitutes a common basis for neoplastic evolution. The most implicit and clinically attractive anticancer strategies, therefore, consist of eliminating tumor cells by preventing their expansion and ultimately inducing apoptotic cell death. We have developed a transgenic mouse model wherein Caspase 3 mediated cell death can be imaged in real time and non-invasively utilizing a luciferase based biosensor. Upon Cre-mediated recombination, transgene expression containing the Caspase 3 biosensor is achieved in a cell or tissue specific manner. Here we show that expression of the Caspase 3 biosensor can be achieved in several tissues. In addition, we demonstrate in mouse models of cancer, that the ability to dynamically and sensitively image the activation of the Caspase 3 provides an opportunity to understand the dynamics of cell death in response to specific drugs or combination therapies. We also provide results demonstrating the utility of the technology in evaluating the efficacy of cancer therapeutics in cancer stem cells, a population that is rare and transient.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2434. doi:1538-7445.AM2012-2434

Assessment of multiexponential diffusion features as MRI cancer therapy response metrics

The aim of this study was to empirically test the effect of chemotherapy-induced tissue changes in a glioma model as measured by several diffusion indices calculated from nonmonoexponential formalisms over a wide range of b-values. We also compared these results to the conventional two-point apparent diffusion coefficient calculation using nominal b-values. Diffusion-weighted imaging was performed over an extended range of b-values (120-4000 sec/mm(2) ) on intracerebral rat 9L gliomas before and after a single dose of 1,3-bis(2-chloroethyl)-1-nitrosourea. Diffusion indices from three formalisms of diffusion-weighted signal decay [(a) two-point analytical calculation using either low or high b-values, (b) a stretched exponential formalism, and (c) a biexponential fit] were tested for responsiveness to therapy-induced differences between control and treated groups. Diffusion indices sensitive to "fast diffusion" produced the largest response to treatment, which resulted in significant differences between groups. These trends were not observed for "slow diffusion" indices. Although the highest rate of response was observed from the biexponential formalism, this was not found to be significantly different from the conventional monoexponential apparent diffusion coefficient method. In conclusion, parameters from the more complicated nonmonoexponential formalisms did not provide additional sensitivity to treatment response in this glioma model beyond that observed from the two-point conventional monoexponential apparent diffusion coefficient method.

Convection enhanced delivery of carboplatin in combination with radiotherapy for the treatment of brain tumors

The purpose of this study was to further evaluate the therapeutic efficacy of convection enhanced delivery (CED) of carboplatin in combination with radiotherapy for treatment of the F98 rat glioma. Tumor cells were implanted stereotactically into the brains of syngeneic Fischer rats, and 13 or 17 d. later carboplatin (20 μg/10 μl) was administered by either CED over 30 min or by Alzet osmotic pumps (0.5 μg/μl/h for 168 h.) beginning at 7 d after tumor implantation. Rats were irradiated with a 15 Gy fractionated dose (5 Gy × 3) of 6 MV photons to the whole brain beginning on the day after drug administration. Other groups of rats received either carboplatin or X-irradiation alone. The tumor carboplatin concentration following CED of 20 μg in 10 μl was 10.4 μg/g, which was equal to that observed following i.v. administration of 100 mg/kg b.w. Rats bearing small tumors, treated with carboplatin and X-irradiation, had a mean survival time (MST) of 83.4 d following CED and 111.8 d following pump delivery with 40% of the latter surviving >180 d (i.e. cured) compared to 55.2 d for CED and 77.2 d. for pump delivery of carboplatin alone and 31.8 d and 24.2 d, respectively, for X-irradiated and untreated controls. There was no microscopic evidence of residual tumor in the brains of all long-term survivors. Not surprisingly, rats with large tumors had much shorter MSTs. Only modest increases in MSTs were observed in animals that received either oral administration or CED of temozolomide plus X-irradiation (23.2 d and 29.3 d) compared to X-irradiation alone. The present survival data, and those previously reported by us, are among the best ever obtained with the F98 glioma model. Initially, they could provide a platform for a Phase I clinical trial to evaluate the safety and potential therapeutic efficacy of CED of carboplatin in patients with recurrent glioblastomas, and ultimately a Phase II trial of carboplatin in combination with radiation therapy.

The brain tumor window model: a combined cranial window and implanted glioma model for evaluating intraoperative contrast agents

OBJECTIVE

Optical contrast agents for brain tumor delineation have been previously evaluated in ex vivo specimens from animals with implanted gliomas and may not reflect the true visual parameters encountered during surgery. This study describes a novel model system designed to evaluate optical contrast agents for tumor delineation in vivo.

METHODS

Biparietal craniectomies were performed on 8-week-old Sprague-Dawley rats. 9L glioma cells were injected intraparenchymally. A cover slip was bonded to the cranial defect with cyanoacrylate glue. When the tumor radius reached 1 mm, Coomassie Blue was administered intravenously while the appearance of the cortical surface was recorded. Computerized image analysis of the red/green/blue color components was used to quantify visible differences between tumor and nonneoplastic tissue and to compare delineation in the brain tumor window (BTW) model with the conventional 9L glioma model.

RESULTS

The tumor margin in the BTW model was poorly defined before contrast administration but readily apparent after contrast administration. Based on red component intensity, tumor delineation improved 4-fold at 50 minutes after contrast administration in the BTW model (P < .002). The conventional 9L glioma model overestimated the degree of delineation compared with the BTW model at the same dose of Coomassie Blue (P < .03).

CONCLUSION

Window placement overlying an implanted glioma is technically possible and well tolerated in the rat. The BTW model is a valid system for evaluating optical contrast agents designed to delineate brain tumor margins. To our knowledge, we have described the first in vivo model system for evaluating optical contrast agents for tumor delineation.

The functional diffusion map: an imaging biomarker for the early prediction of cancer treatment outcome

Functional diffusion map (fDM) has been recently reported as an early and quantitative biomarker of clinical brain tumor treatment outcome. This approach spatially maps and quantifies treatment-induced changes in tumor water diffusion values resulting from alterations in cell density/cell membrane function and microenvironment. This current study was designed to evaluate the capability of fDM for preclinical evaluation of dose escalation studies and to determine if these changes were correlated with outcome measures (cell kill and overall survival). Serial T2-weighted were carried out on rodents with orthotopically implanted 9L brain tumors receiving three doses of 1,3-bis(2-chloroethyl)-1-nitrosourea (6.65, 13.3, and 26.6 mg/kg, i.p.). All images were coregistered to baseline T2-weighted images for fDM analysis. Analysis of tumor fDM data on day 4 posttreatment detected dose-dependent changes in tumor diffusion values, which were also found to be spatially dependent. Histologic analysis of treated tumors confirmed spatial changes in cellularity as observed by fDM. Early changes in tumor diffusion values were found to be highly correlative with drug dose and independent biologic outcome measures (cell kill and survival). Therefore, The fDM imaging biomarker for early prediction of treatment efficacy can be used in the drug development process.

Dynamic imaging of emerging resistance during cancer therapy

One of the greatest challenges in developing therapeutic regimens is the inability to rapidly and objectively assess tumor response due to treatment. Moreover, tumor response to therapeutic intervention in many cases is transient, and progressive alterations within the tumor may mask the effectiveness of an initially successful therapy. The ability to detect these changes as they occur would allow timely initiation of alternative approaches, maximizing therapeutic outcome. We investigated the ability of diffusion magnetic resonance imaging (MRI) to provide a sensitive measure of tumor response throughout the course of treatment, possibly identifying changes in sensitivity to the therapy. Orthotopic 9L gliomas were subjected to two separate therapeutic regimens, with one group receiving a single 5-day cycle (1omega) of low-dose 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU) and a second group receiving two cycles at the same dose, bisected with 2 days of rest (2omega). Apparent diffusion coefficient maps were acquired before and throughout treatment to observe changes in water mobility, and these observations were correlated to standard measures of therapeutic response and outcome. Our results showed that diffusion MRI was indeed able to detect the emergence of a drug-resistant tumor subpopulation subsequent to an initially successful cycle of BCNU therapy, leading to minimal gains from a second cycle. These diffusion MRI findings were highly correlated with tumor growth delay, animal survival, and ex vivo growth inhibition assays showing emerging resistance in excised tumors. Overall, this study highlights the ability of diffusion MRI to provide sensitive dynamic assessment of therapy-induced response, allowing early opportunities for optimization of therapeutic protocols.