Bone Marrow and Tumor Radiomics at F-FDG PET/CT: Impact on Outcome Prediction in Non-Small Cell Lung Cancer.

Background Primary tumor maximum standardized uptake value is a prognostic marker for non-small cell lung cancer. In the setting of malignancy, bone marrow activity from fluorine 18-fluorodeoxyglucose (FDG) PET may be informative for clinical risk stratification. Purpose To determine whether integrating FDG PET radiomic features of the primary tumor, tumor penumbra, and bone marrow identifies lung cancer disease-free survival more accurately than clinical features alone.

[18F] FDG Positron Emission Tomography (PET) Tumor and Penumbra Imaging Features Predict Recurrence in Non-Small Cell Lung Cancer.

We identified computational imaging features on 18F-fluorodeoxyglucose positron emission tomography (PET) that predict recurrence/progression in non-small cell lung cancer (NSCLC). We retrospectively identified 291 patients with NSCLC from 2 prospectively acquired cohorts (training, n = 145; validation, n = 146). We contoured the metabolic tumor volume (MTV) on all pretreatment PET images and added a 3-dimensional penumbra region that extended outward 1 cm from the tumor surface.

Circulating tumor microemboli diagnostics for patients with non-small-cell lung cancer.

Introduction: Circulating tumor microemboli (CTM) are potentially important cancer biomarkers, but using them for cancer detection in early-stage disease has been assay limited. We examined CTM test performance using a sensitive detection platform to identify stage I non-small-cell lung cancer (NSCLC) patients undergoing imaging evaluation.

Methods: First, we prospectively enrolled patients during 18F-FDG PET-CT imaging evaluation for lung cancer that underwent routine phlebotomy where CTM and circulating tumor cells (CTCs) were identified in blood using nuclear (DAPI), cytokeratin (CK), and CD45 immune-fluorescent antibodies followed by morphologic identification.

Survival and death signals can predict tumor response to therapy after oncogene inactivation.

Cancers can exhibit marked tumor regression after oncogene inhibition through a phenomenon called "oncogene addiction." The ability to predict when a tumor will exhibit oncogene addiction would be useful in the development of targeted therapeutics. Oncogene addiction is likely the consequence of many cellular programs.

SPECT and PET imaging of EGF receptors with site-specifically labeled EGF and dimeric EGF.

We describe a new generation of tracers for molecular imaging of the cell surface receptors for epidermal growth factor (EGF). These receptors play a key role in the progression of many tumors and are major drug development targets. Our tracers are based on a recombinant human EGF expressed with a cysteine-containing tag that enables facile site-specific radiolabeling with (99m)Tc for single photon emission computed tomography or site-specific conjugation of (64)Cu PEGylated chelators for positron emission tomography.

Progressive Dyspnea After CABG: Complication of Retained Epicardial Pacing Wires.

We report a case of progressive dyspnea and recurrent pneumonia after uneventful coronary artery bypass graft surgery caused by migration of retained epicardial pacing wires into the right upper lobe of the lung. Removal of the wires by open thoracotomy resulted in significant improvement in dyspnea and near complete resolution of the bronchiectasis and consolidation.

Combined Inactivation of MYC and K-Ras oncogenes reverses tumorigenesis in lung adenocarcinomas and lymphomas.

Background: Conditional transgenic models have established that tumors require sustained oncogene activation for tumor maintenance, exhibiting the phenomenon known as "oncogene-addiction." However, most cancers are caused by multiple genetic events making it difficult to determine which oncogenes or combination of oncogenes will be the most effective targets for their treatment.

Methodology/principal Findings: To examine how the MYC and K-ras(G12D) oncogenes cooperate for the initiation and maintenance of tumorigenesis, we generated double conditional transgenic tumor models of lung adenocarcinoma and lymphoma.