Standardization in Quantitative Imaging: A Multicenter Comparison of Radiomic Features from Different Software Packages on Digital Reference Objects and Patient Data Sets.

Radiomic features are being increasingly studied for clinical applications. We aimed to assess the agreement among radiomic features when computed by several groups by using different software packages under very tightly controlled conditions, which included standardized feature definitions and common image data sets. Ten sites (9 from the NCI's Quantitative Imaging Network] positron emission tomography-computed tomography working group plus one site from outside that group) participated in this project. Nine common quantitative imaging features were selected for comparison including features that describe morphology, intensity, shape, and texture. The common image data sets were: three 3D digital reference objects (DROs) and 10 patient image scans from the Lung Image Database Consortium data set using a specific lesion in each scan. Each object (DRO or lesion) was accompanied by an already-defined volume of interest, from which the features were calculated. Feature values for each object (DRO or lesion) were reported. The coefficient of variation (CV), expressed as a percentage, was calculated across software packages for each feature on each object. Thirteen sets of results were obtained for the DROs and patient data sets. Five of the 9 features showed excellent agreement with CV < 1%; 1 feature had moderate agreement (CV < 10%), and 3 features had larger variations (CV ≥ 10%) even after attempts at harmonization of feature calculations. This work highlights the value of feature definition standardization as well as the need to further clarify definitions for some features.

Comparison of established and emerging biodosimetry assays.

Rapid biodosimetry tools are required to assist with triage in the case of a large-scale radiation incident. Here, we aimed to determine the dose-assessment accuracy of the well-established dicentric chromosome assay (DCA) and cytokinesis-block micronucleus assay (CBMN) in comparison to the emerging γ-H2AX foci and gene expression assays for triage mode biodosimetry and radiation injury assessment. Coded blood samples exposed to 10 X-ray doses (240 kVp, 1 Gy/min) of up to 6.4 Gy were sent to participants for dose estimation. Report times were documented for each laboratory and assay. The mean absolute difference (MAD) of estimated doses relative to the true doses was calculated. We also merged doses into binary dose categories of clinical relevance and examined accuracy, sensitivity and specificity of the assays. Dose estimates were reported by the first laboratories within 0.3-0.4 days of receipt of samples for the γ-H2AX and gene expression assays compared to 2.4 and 4 days for the DCA and CBMN assays, respectively. Irrespective of the assay we found a 2.5-4-fold variation of interlaboratory accuracy per assay and lowest MAD values for the DCA assay (0.16 Gy) followed by CBMN (0.34 Gy), gene expression (0.34 Gy) and γ-H2AX (0.45 Gy) foci assay. Binary categories of dose estimates could be discriminated with equal efficiency for all assays, but at doses ≥1.5 Gy a 10% decrease in efficiency was observed for the foci assay, which was still comparable to the CBMN assay. In conclusion, the DCA has been confirmed as the gold standard biodosimetry method, but in situations where speed and throughput are more important than ultimate accuracy, the emerging rapid molecular assays have the potential to become useful triage tools.

Laboratory intercomparison of gene expression assays.

The possibility of a large-scale acute radiation exposure necessitates the development of new methods that could provide rapid individual dose estimates with high sample throughput. The focus of the study was an intercomparison of laboratories' dose-assessment performances using gene expression assays. Lithium-heparinized whole blood from one healthy donor was irradiated (240 kVp, 1 Gy/min) immediately after venipuncture at approximately 37°C using single X-ray doses. Blood samples to establish calibration curves (0.25-4 Gy) as well as 10 blinded test samples (0.1-6.4 Gy) were incubated for 24 h at 37°C supplemented with an equal volume of medium and 10% fetal calf serum. For quantitative reverse transcription polymerase chain reaction (qRT-PCR), samples were lysed, stored at -20°C and shipped on ice. For the Chemical Ligation Dependent Probe Amplification methodology (CLPA), aliquots were incubated in 2 ml CLPA reaction buffer (DxTerity), mixed and shipped at room temperature. Assays were run in each laboratory according to locally established protocols. The mean absolute difference (MAD) of estimated doses relative to the true doses (in Gy) was calculated. We also merged doses into binary categories reflecting aspects of clinical/diagnostic relevance and examined accuracy, sensitivity and specificity. The earliest reported time on dose estimates was <8 h. The standard deviation of technical replicate measurements in 75% of all measurements was below 11%. MAD values of 0.3-0.5 Gy and 0.8-1.3 Gy divided the laboratories contributions into two groups. These fourfold differences in accuracy could be primarily explained by unexpected variances of the housekeeping gene (P = 0.0008) and performance differences in processing of calibration and blinded test samples by half of the contributing laboratories. Reported gene expression dose estimates aggregated into binary categories in general showed an accuracies and sensitivities of 93-100% and 76-100% for the groups, with low MAD and high MAD, respectively. In conclusion, gene expression-based dose estimates were reported quickly, and for laboratories with MAD between 0.3-0.5 Gy binary dose categories of clinical significance could be discriminated with an accuracy and sensitivity comparable to established cytogenetic assays.

Genomic profiles and predictive biological networks in oxidant-induced atherogenesis.

Atherogenic stimuli trigger complex responses in vascular smooth muscle cells (VSMCs) that culminate in activation/repression of overlapping signal transduction cascades involving oxidative stress. In the case of benzo[a]pyrene (BaP), a polycyclic aromatic hydrocarbon present in tobacco smoke, the atherogenic response involves interference with redox homeostasis by oxidative intermediates of BaP metabolism. The present studies were conducted to define genomic profiles and predictive gene biological networks associated with the atherogenic response of murine (aortic) VSMCs to BaP. A combined oxidant-antioxidant treatment regimen was used to identify redox-sensitive targets during the early course of the atherogenic response. Gene expression profiles were defined using cDNA microarrays coupled to analysis of variance and several clustering methodologies. A predictor algorithm was then applied to gain insight into critical gene-gene interactions during atherogenesis. Supervised and nonsupervised analyses identified clones highly regulated by BaP, unaffected by antioxidant, and neutralized by combined chemical treatments. Lymphocyte antigen-6 complex, histocompatibility class I component factors, secreted phosphoprotein, and several interferon-inducible proteins were identified as novel redox-regulated targets of BaP. Predictor analysis confirmed these relationships and identified immune-related genes as critical molecular targets of BaP. Redox-dependent patterns of gene deregulation indicate that oxidative stress plays a prominent role during the early stages of BaP-induced atherogenesis.