Purpose:To identify quantitative imaging biomarkers at fluorine 18 ( 18 F) positron emission tomography (PET) for predicting distant metastasis in patients with early-stage non-small cell lung cancer (NSCLC). Materials andMethods:In this institutional review board-approved HIPAA-compliant retrospective study, the pretreatment 18 F fluorodeoxyglucose PET images in 101 patients treated with stereotactic ablative radiation therapy from 2005 to 2013 were analyzed. Data for 70 patients who were treated before 2011 were used for discovery purposes, while data from the remaining 31 patients were used for independent validation. Quantitative PET imaging characteristics including statistical, histogram-related, morphologic, and texture features were analyzed, from which 35 nonredundant and robust features were further evaluated. Cox proportional hazards regression model coupled with the least absolute shrinkage and selection operator was used to predict distant metastasis. Whether histologic type provided complementary value to imaging by combining both in a single prognostic model was also assessed. Results:The optimal prognostic model included two image features that allowed quantification of intratumor heterogeneity and peak standardized uptake value. In the independent validation cohort, this model showed a concordance index of 0.71, which was higher than those of the maximum standardized uptake value and tumor volume, with concordance indexes of 0.67 and 0.64, respectively. The prognostic model also allowed separation of groups with low and high risk for developing distant metastasis (hazard ratio, 4.8; P = .0498, log-rank test), which compared favorably with maximum standardized uptake value and tumor volume (hazard ratio, 1.5 and 2.0, respectively; P = .73 and 0.54, log-rank test, respectively). When combined with histologic types, the prognostic power was further improved (hazard ratio, 6.9; P = .0289, log-rank test; and concordance index, 0.80). Conclusion:PET imaging characteristics associated with distant metastasis that could potentially help practitioners to tailor appropriate therapy for individual patients with earlystage NSCLC were identified.q RSNA, 2016

MRI significantly improves the accuracy and reliability of target delineation in radiation therapy for certain tumors due to its superior soft tissue contrast compared to CT. A treatment planning process with MRI as the sole imaging modality will eliminate systematic CT/MRI co-registration errors, reduce cost and radiation exposure, and simplify clinical workflow. However, MRI lacks the key electron density information necessary for accurate dose calculation and generating reference images for patient setup. The purpose of this work is to develop a unifying method to derive electron density from standard T1-weighted MRI. We propose to combine both intensity and geometry information into a unifying probabilistic Bayesian framework for electron density mapping. For each voxel, we compute two conditional probability density functions (PDFs) of electron density given its: (1) T1-weighted MRI intensity, and (2) geometry in a reference anatomy, obtained by deformable image registration between the MRI of the atlas and test patient. The two conditional PDFs containing intensity and geometry information are combined into a unifying posterior PDF, whose mean value corresponds to the optimal electron density value under the mean-square error criterion. We evaluated the algorithm's accuracy of electron density mapping and its ability to detect bone in the head for 8 patients, using an additional patient as the atlas or template. Mean absolute HU error between the estimated and true CT, as well as ROC's for bone detection (HU>200) were calculated. The performance was compared with a global intensity approach based on T1 and no density correction (set whole head to water). The proposed technique significantly reduced the errors in electron density estimation, with a mean absolute HU error of 126, compared with 139 for deformable registration (p=2×10-4), 283 for the intensity approach (p=2×10-6) and 282 without density correction (p=5×10-6). For 90% sensitivity in bone detection, the proposed method achieved a specificity of 86%, compared with 80%, 11% and 10% using deformable registration, intensity and without density correction, respectively. Notably, the Bayesian approach was more robust against anatomical differences between patients, with a specificity of 62% in the worst case (patient), compared to 30% specificity in registration-based approach. In conclusion, the proposed unifying Bayesian method provides accurate electron density estimation and bone detection from MRI of the head with highly heterogeneous anatomy.

As tissue engineering products move toward the clinic, nondestructive methods to monitor their development and ensure quality are needed. In this study, high-resolution spectral ultrasound imaging (SUSI) was used to noninvasively characterize mineral content in collagen hydrogels. SUSI was used to generate three-dimensional (3D) grayscale (GS) images of construct morphology with submillimeter resolution. Spectral analysis of the backscattered radio frequency (RF) ultrasound signals was used to determine the midband fit (MBF) and slope of the linearized RF spectrum. These parameters are operator and instrument independent, and were used to characterize the spatial distribution of mineral in constructs supplemented with hydroxyapatite particles. GS and MBF correlated closely with mineral content, while slope was not dependent on concentration. SUSI also was used to monitor mineralization of collagen constructs by immersion in simulated body fluid (SBF) over 21 days. The construct surface was mineralized before the interior, and there was a dose-dependent effect of SBF concentration on degree of mineralization and deposited particle size. MBF density was closely correlated with the amount of calcium deposited. These data demonstrate that SUSI has utility as a noninvasive imaging method for quantitative analysis of mineralization in 3D protein constructs. Such techniques may assist the development of engineered orthopedic tissues.

The study of mechanotransduction relies on tools that are capable of applying mechanical forces to elicit and assess cellular responses. Here we report a new (to our knowledge) technique, called two-bubble acoustic tweezing cytometry (TB-ATC), for generating spatiotemporally controlled subcellular mechanical forces on live cells by acoustic actuation of paired microbubbles targeted to the cell adhesion receptor integrin. By measuring the ultrasound-induced activities of cell-bound microbubbles and the actin cytoskeleton contractile force responses, we determine that TB-ATC elicits mechanoresponsive cellular changes via cyclic, paired displacements of integrin-bound microbubbles driven by the attractive secondary acoustic radiation force (sARF) between the bubbles in an ultrasound field. We demonstrate the feasibility of dual-mode TB-ATC for both subcellular probing and mechanical stimulation. By exploiting the robust and unique interaction of ultrasound with microbubbles, TB-ATC provides distinct advantages for experimentation and quantification of applied forces and cellular responses for biomechanical probing and stimulation of cells.

Non-destructive monitoring of engineered tissues is needed for translation of these products from the lab to the clinic. In this study, non-invasive, high resolution spectral ultrasound imaging (SUSI) was used to monitor the differentiation of MC3T3 pre-osteoblasts seeded within collagen hydrogels. SUSI was used to measure the diameter, concentration and acoustic attenuation of scatterers within such constructs cultured in either control or osteogenic medium over 21 days. Conventional biochemical assays were used on parallel samples to determine DNA content and calcium deposition. Construct volume and morphology were accurately imaged using ultrasound. Cell diameter was estimated to be approximately 12.5–15.5 µm using SUSI, which corresponded well to measurements of fluorescently stained cells. The total number of cells per construct assessed by quantitation of DNA content decreased from 5.6±2.4×104 at day 1 to 0.9±0.2×104 at day 21. SUSI estimation of the equivalent number of acoustic scatters showed a similar decreasing trend, except at day 21 in the osteogenic samples, which showed a marked increase in both scatterer number and acoustic impedance, suggestive of mineral deposition by the differentiating MC3T3 cells. Estimation of calcium content by SUSI was 41.7±11.4 µg/ml, which agreed well with the biochemical measurement of 38.7±16.7 µg/ml. Color coded maps of parameter values were overlaid on B-mode images to show spatiotemporal changes in cell diameter and calcium deposition. This study demonstrates the use of non-destructive ultrasound imaging to provide quantitative information on the number and differentiated state of cells embedded within 3D engineered constructs, and therefore presents a valuable tool for longitudinal monitoring of engineered tissue development.