In diffuse large B-cell lymphoma (DLBCL), the clinical and biological significance of concordant and discordant bone marrow (BM) involvement have not been well investigated. We evaluated 712 de novo DLBCL patients with front-line rituximab-containing treatment, including 263 patients with positive and 449 with negative BM status. Compared with negative BM disease, concordant BM adversely impacted overall and progression-free survival, probably independent of the International Prognostic Index (IPI) and cell-of-origin classification. Once BM is concordantly involved, poor prognosis was not associated with the extent of BM involvement. Conversely, patients with discordant BM showed favorable overall survival similar to stage I-II DLBCL. A BM-adjusted IPI, using three parameters: concordant BM involvement, age >60 years, and performance status >1, improves the risk stratification for DLBCL with positive BM. Intensive immunochemotherapy seemingly rendered survival benefit for patients with concordant BM, as did rituximab maintenance for the discordant BM group. Frequently revealing adverse clinical and molecular characteristics, patients with concordant BM demonstrated gene expression signatures relevant to tumor cell proliferation, migration, and immune escape. In conclusion, clinical and biological heterogeneity is seen in DLBCL with positive BM but concordant BM involvement represents a distinct subset with unfavorable gene signatures, high-risk clinicopathologic features, and poor prognosis.
Purpose: To investigate whether a strong magnetic field (B=1.5 T) can affect dose responses of thermoluminescent dosimeters (TLDs), optically stimulated luminescence dosimeters (OSLDs) and Gafchromic films using an MR‐Linac (Elekta) before and after the magnet was ramped down from 1.5 T to 0 T. Methods: Three types of dosimeters (TLDs, OSLDs, EBT3 films) were divided into two groups. Group 1 was first irradiated in a phantom of Solid Water slabs (Standard Imaging) inside a B=1.5 T field with a 7 MV beam from an MR‐Linac system. The radiation output at the location of the dosimeters (isocenter at 10 cm depth) was measured using an ion chamber (NE2571, Phoenix Dosimetry). Three doses (150, 300, 600 MU, corresponding to 1.18, 2.36, and 4.74 Gy) were delivered to the dosimeters. A week later the MR magnet was ramped down to zero field and dosimeters in Group 2 were irradiated with the same MUs. Dosimeters of each type were read out during the same session (about 4 weeks post irradiation in the B field, and 3 weeks with no B field). The ratios of signals between Group 1 and Group 2 were calculated. Results: Radiation output measured with the chamber was within 1% before and after ramping down the MR magnet. For TLDs, the ratio of signals with B field to signals without B field averaged over three dose levels was 1.003±0.016; for OSLDs, the ratio was 0.994±0.022; for films, the ratios of two batches (different manufacturing dates) were 0.997 and 0.985. Conclusion: Dose responses of all three dosimeters seem not affected by the presence of a 1.5 T magnetic field within uncertainty of ∼2%. More measurements will be conducted to test reproducibility. We acknowledge research support from Elekta AB.
Background: Conventional MRI poses unique challenges in quantitative analysis due to a lack of specific physical meaning for voxel intensity values. In recent years, intensity standardization methods to optimize MRI signal consistency have been developed to address this problem. However, the effects of standardization methods on the head and neck region have not been previously investigated. Purpose: This study proposes a workflow based on healthy tissue region of interest (ROI) analysis to determine intensity consistency within a patient cohort. Through this workflow, we systematically evaluate different intensity standardization methods for T2-weighted MRI of the head and neck region. Methods: Two image cohorts of five head and neck cancer patients, one with heterogeneous acquisition parameters (median age 59 years [range, 53-61]), and another with homogeneous acquisition parameters from a clinical trial (NCT04265430) (median age 61 years [range, 54-77]) were retrospectively analyzed. The standard deviation of cohort-level normalized mean intensity (SD NMIc), a metric of intensity consistency, was calculated across ROIs to determine the effect of five intensity standardization methods on T2-weighted images. For each cohort, the Friedman test with a subsequent post-hoc Bonferroni-corrected Wilcoxon signed-rank test was conducted to compare SD NMIc among methods. Results: Consistency (SD NMIc across ROIs) between T2-weighted images is substantially more impaired in the cohort with heterogeneous acquisition parameters (0.28 +- 0.04) than in the cohort with homogeneous acquisition parameters (0.15 +- 0.05). Consequently, intensity standardization methods more significantly improve consistency in the cohort with heterogeneous acquisition parameters (corrected p < 0.005 for all methods compared to no standardization) than in the cohort with homogeneous acquisition parameters (corrected p > 0.05 for all methods compared to no standardization). Conclusions: Our findings stress the importance of image acquisition parameter standardization, together with the need for testing intensity consistency before performing quantitative analysis of MRI.
The mechanism of Alzheimer's disease (AD) remains elusive, partly due to the incomplete identification of risk genes. We developed an approach to predict AD-associated genes by learning the functional pattern of curated AD-associated genes from brain gene networks. We created a pipeline to evaluate disease-gene association by interrogating heterogeneous biological networks at different molecular levels. Our analysis showed that top-ranked genes were functionally related to AD. We identified gene modules associated with AD pathways, and found that top-ranked genes were correlated with both neuropathological and clinical phenotypes of AD on independent datasets. We also identified potential causal variants for genes such as FYN and PRKAR1A by integrating brain eQTL and ATAC-seq data. Lastly, we created the ALZLINK web interface, enabling users to exploit the functional relevance of predicted genes to AD. The predictions and pipeline could become a valuable resource to advance the identification of therapeutic targets for AD. Keywords: Alzheimer's disease; disease gene prediction; functional gene networks
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