Quantitative imaging feature pipeline: a web-based tool for utilizing, sharing, and building image-processing pipelines.

Quantitative image features that can be computed from medical images are proving to be valuable biomarkers of underlying cancer biology that can be used for assessing treatment response and predicting clinical outcomes. However, validation and eventual clinical implementation of these tools is challenging due to the absence of shared software algorithms, architectures, and the tools required for computing, comparing, evaluating, and disseminating predictive models. Similarly, researchers need to have programming expertise in order to complete these tasks.

Isoflavones as Ah Receptor Agonists in Colon-Derived Cell Lines: Structure-Activity Relationships.

Many of the protective responses observed for flavonoids in the gastrointestinal track resemble aryl hydrocarbon receptor (AhR)-mediated effects. Therefore, we examined the structure-activity relationships of isoflavones and isomeric flavone and flavanones as AhR ligands on the basis of their induction of CYP1A1, CYP1B1, and UGT1A1 gene expression in colon cancer Caco2 cells and young adult mouse colonocyte (YAMC) cells. Caco2 cells were significantly more Ah-responsive than YAMC cells, and this was due, in part, to flavonoid-induced cytotoxicity in the latter cell lines.

[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.

A radiogenomic dataset of non-small cell lung cancer.

Medical image biomarkers of cancer promise improvements in patient care through advances in precision medicine. Compared to genomic biomarkers, image biomarkers provide the advantages of being non-invasive, and characterizing a heterogeneous tumor in its entirety, as opposed to limited tissue available via biopsy. We developed a unique radiogenomic dataset from a Non-Small Cell Lung Cancer (NSCLC) cohort of 211 subjects.