On-board cone-beam computed tomography (CBCT) has recently become available to provide volumetric information of a patient in the treatment position, and holds promises for improved target localization and irradiation dose verification. The design of currently available on-board CBCT, however, is far from optimal. Its quality is adversely influenced by many factors, such as scatter, beam hardening, and intra-scanning organ motion. In this work we quantitatively study the influence of organ motion on CBCT imaging and investigate a strategy to acquire high quality phase-resolved [four-dimensional (4D)] CBCT images based on phase binning of the CBCT projection data. An efficient and robust method for binning CBCT data according to the patient's respiratory phase derived in the projection space was developed. The phase-binned projections were reconstructed using the conventional Feldkamp algorithm to yield 4D CBCT images. Both phantom and patient studies were carried out to validate the technique and to optimize the 4D CBCT data acquisition protocol. Several factors that are important to the clinical implementation of the technique, such as the image quality, scanning time, number of projections, and radiation dose, were analyzed for various scanning schemes. The general references drawn from this study are: (i) reliable phase binning of CBCT projections is accomplishable with the aid of external or internal marker and simple analysis of its trace in the projection space, and (ii) artifact-free 4D CBCT images can be obtained without increasing the patient radiation dose as compared to the current 3D CBCT scan.

Purpose Radiotherapy (RT) can result in lymphopenia, which has been linked to poorer survival. Here, we test the hypothesis that RT-induced lymphopenia is mediated by a tumor-secreted factor, Galectin-1 (Gal-1), which possesses T-cell pro-apoptotic activities. Experimental Design Matched Gal-1 wildtype or null mice were implanted with Lewis Lung carcinoma (LLC-1) that either expressed Gal-1 or had Gal-1 stably down-regulated. Tumors were irradiated locally and circulating Gal-1 and T-cells were measured. Tumor growth, lung metastasis, intratumoral T-cell apoptosis, and microvessel density count were quantified. Thiodigalatoside (TDG), a Gal-1 inhibitor, was used to inhibit Gal-1 function in another group of mice to validate the observations noted with Gal-1 down-regulation. Lymphocyte counts, survival and plasma Gal-1 were analyzed in cohorts of RT-treated lung (NSCLC) and head and neck cancer patients. Results LLC irradiation increased Gal-1 secretion and decreased circulating T-cells in mice, regardless of host Gal-1 expression. Inhibition of tumor Gal-1 with either shRNA or TDG ablated RT-induced lymphopenia. Irradiated shGal-1 tumors showed significantly less intratumoral CD8+ T-cell apoptosis and microvessel density, which led to marked tumor growth delay and reduced lung metastasis compared to controls. Similar observations were made after TDG treatment. RT-induced lymphopenia was associated with poorer overall survival in NSCLC patients treated with hypofractionated RT. Plasma Gal-1 increased while T-cell decreased after radiation in another group of patients. Conclusions RT-related systemic lymphopenia appeared to be mediated by RT-induced tumor Gal-1 secretion that could lead to tumor progression through intratumoral immune suppression and enhanced angiogenesis.

Plasmablastic lymphoma (PBL), an aggressive non-Hodgkin's lymphoma that carries a poor prognosis, previously has been identified almost exclusively in patients infected with the human immunodeficiency virus (HIV). We present a case of a 42-year-old HIV-negative patient presenting with an isolated nasal cavity mass, the typical presentation for PBL. The patient was given systemic chemotherapy, central nervous system prophylaxis, and consolidative locoregional radiotherapy and achieved a complete clinical response. This case suggests PBL should be considered in HIV-negative patients with characteristic findings.

Prognostic biomarkers that can reliably predict early disease progression of non-small cell lung cancer (NSCLC) are needed for identifying those patients at high risk for progression, who may benefit from more intensive treatment. In this work, we aimed to identify an imaging signature for predicting progression-free survival (PFS) of locally advanced NSCLC. Methods : This retrospective study included 82 patients with stage III NSCLC treated with definitive chemoradiotherapy for whom both baseline and mid-treatment PET/CT scans were performed. They were randomly placed into two groups: training cohort (n=41) and testing cohort (n=41). All primary tumors and involved lymph nodes were delineated. Forty-five quantitative imaging features were extracted to characterize the tumors and involved nodes at baseline and mid-treatment as well as differences between two scans performed at these two points. An imaging signature was developed to predict PFS by fitting an L1-regularized Cox regression model. Results : The final imaging signature consisted of three imaging features: the baseline tumor volume, the baseline maximum distance between involved nodes, and the change in maximum distance between the primary tumor and involved nodes measured at two time points. According to multivariate analysis, the imaging model was an independent prognostic factor for PFS in both the training (hazard ratio [HR], 1.14, 95% confidence interval [CI], 1.04-1.24; P = 0.003), and testing (HR, 1.21, 95% CI, 1.10-1.33; P = 0.048) cohorts. The imaging signature stratified patients into low- and high-risk groups, with 2-year PFS rates of 61.9% and 33.2%, respectively ( P = 0.004 [log-rank test]; HR, 4.13, 95% CI, 1.42-11.70) in the training cohort, as well as 43.8% and 22.6%, respectively ( P = 0.006 [log-rank test]; HR, 3.45, 95% CI, 1.35-8.83) in the testing cohort. In both cohorts, the imaging signature significantly outperformed conventional imaging metrics, including tumor volume and SUV max value (C-indices: 0.77-0.79 for imaging signature, and 0.53-0.73 for conventional metrics). Conclusions : Evaluation of early treatment response by combining primary tumor and nodal imaging characteristics may improve the prediction of PFS of locally advanced NSCLC patients.