Disease Progression Modelling in Chronic Obstructive Pulmonary Disease (COPD)

RATIONALE: The decades-long progression of Chronic Obstructive Pulmonary Disease (COPD) renders identifying different trajectories of disease progression challenging. OBJECTIVES: To identify subtypes of COPD patients 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 CT imaging markers in 3698 GOLD1-4 patients and 3479 controls from the COPDGene study to identify COPD patient subtypes. We confirmed the identified subtypes and progression patterns using ECLIPSE 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=2354, 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 non-baseline 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'

DW-MRI as a Biomarker to Compare Therapeutic Outcomes in Radiotherapy Regimens Incorporating Temozolomide or Gemcitabine in Glioblastoma

The effectiveness of the radiosensitizer gemcitabine (GEM) was evaluated in a mouse glioma along with the imaging biomarker diffusion-weighted magnetic resonance imaging (DW-MRI) for early detection of treatment effects. A genetically engineered murine GBM model [Ink4a-Arf−/− PtenloxP/loxP/Ntv-a RCAS/PDGF(+)/Cre(+)] was treated with gemcitabine (GEM), temozolomide (TMZ) +/− ionizing radiation (IR). Therapeutic efficacy was quantified by contrast-enhanced MRI and DW-MRI for growth rate and tumor cellularity, respectively. Mice treated with GEM, TMZ and radiation showed a significant reduction in growth rates as early as three days post-treatment initiation. Both combination treatments (GEM/IR and TMZ/IR) resulted in improved survival over single therapies. Tumor diffusion values increased prior to detectable changes in tumor volume growth rates following administration of therapies. Concomitant GEM/IR and TMZ/IR was active and well tolerated in this GBM model and similarly prolonged median survival of tumor bearing mice. DW-MRI provided early changes to radiosensitization treatment warranting evaluation of this imaging biomarker in clinical trials

The distribution of the apparent diffusion coefficient as an indicator of the response to chemotherapeutics in ovarian tumour xenografts

Cancer Council of Queensland and a mobility grant (Personalized Medicine) from the German Academic Exchange Service (DAAD)