A Mathematical Model of Tumor Volume Changes during Radiotherapy

Purpose. To develop a clinically viable mathematical model that quantitatively predicts tumor volume change during radiotherapy in order to provide treatment response assessment for prognosis, treatment plan optimization, and adaptation. Method and Materials. The correction factors containing hypoxia, DNA single strand breaks, potentially lethal damage, and other factors were used to develop an improved cell survival model based on the popular linear-quadratic model of cell survival in radiotherapy. The four-level cell population model proposed by Chvetsov et al. was further simplified by removing the initial hypoxic fraction and reoxygenation parameter, which are hard to obtain in routine clinics, such that an easy-to-use model can be developed for clinical applications. The new model was validated with data of nine lung and cervical cancer patients. Results. Out of the nine cases, the new model can predict tumor volume change in six cases with a correlation index R2 greater than 0.9 and the rest of three with R2 greater than 0.85. Conclusion. Based on a four-level cell population model, a more practical and simplified cell survival curve was proposed to model the tumor volume changes during radiotherapy. Validation study with patient data demonstrated feasibility and clinical usefulness of the new model in predicting tumor volume change in radiotherapy

Inequalities related to the S-Divergence

The S-Divergence is a distance like function on the convex cone of positive definite matrices, which is motivated from convex optimization. In this paper, we will prove some inequalities for Kubo-Ando means with respect to the square root of the S-Divergence

Quantitative assessment of image motion blur in diffraction images of moving biological cells

Motion blur (MB) presents a significant challenge for obtaining high-contrast image data from biological cells with a polarization diffraction imaging flow cytometry (p-DIFC) method. A new p-DIFC experimental system has been developed to evaluate the MB and its effect on image analysis using a time-delay-integration (TDI) CCD camera. Diffraction images of MCF-7 and K562 cells have been acquired with different speed-mismatch ratios and compared to characterize MB quantitatively. Frequency analysis of the diffraction images shows that the degree of MB can be quantified by bandwidth variations of the diffraction images along the motion direction. The analytical results were confirmed by the p-DIFC image data acquired at different speed-mismatch ratios and used to validate a method of numerical simulation of MB on blur-free diffraction images, which provides a useful tool to examine the blurring effect on diffraction images acquired from the same cell. These results provide insights on the dependence of diffraction image on MB and allow significant improvement on rapid biological cell assay with the p-DIFC method

TAT-Modified Gold Nanoparticles Enhance the Antitumor Activity of PAD4 Inhibitors

Purpose: Histone citrullination by peptidylarginine deiminases 4 (PAD4) regulates the gene expression of tumor suppressor. In our previously study, YW3-56 (356) was developed as a potent PAD4 inhibitor for cancer therapy with novel function in the autophagy pathway. To enhance the antitumor activity, the PAD4 inhibitor 356 was modified by the well-established cationic penetrating peptide RKKRRQRRR (peptide TAT) and gold nanoparticles to obtain 356-TAT-AuNPs which could enhance the permeability of chemical drug in solid tumor. Methods: 356-TAT-AuNPs were prepared, and their morphology were characterized. The antitumor activity of 356-TAT-AuNPs was evaluated in vitro and in vivo. Results: 356-TAT-AuNPs exhibited higher anticancer activity against HCT-116, MCF-7 and A549 cells than 356 and 356-AuNPs. Compared with 356 and 356-AuNPs, 356-TAT-AuNPs entered the cytoplasm and nuclear, exhibited stronger anticancer activity by increasing apoptosis, inducing autophagy and inhibiting of histone H3 citrullination, and in HCT-116 xenograft mouse model, 356-TAT-AuNPs could improve the antitumor activity. Conclusion: The modified AuNPs with peptide TAT as drug delivery system are potent in delaying tumor growth and could be a powerful vehicle for profitable anticancer drug development. We believe that peptide TAT modification strategy may provide a simple and valuable method for improving antitumor activity of PAD4 inhibitors for clinical use.publishedVersio

A Tri-Modality Image Fusion Method for Target Delineation of Brain Tumors in Radiotherapy

Purpose To develop a tri-modality image fusion method for better target delineation in image-guided radiotherapy for patients with brain tumors. Methods A new method of tri-modality image fusion was developed, which can fuse and display all image sets in one panel and one operation. And a feasibility study in gross tumor volume (GTV) delineation using data from three patients with brain tumors was conducted, which included images of simulation CT, MRI, and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) examinations before radiotherapy. Tri-modality image fusion was implemented after image registrations of CT+PET and CT+MRI, and the transparency weight of each modality could be adjusted and set by users. Three radiation oncologists delineated GTVs for all patients using dual-modality (MRI/CT) and tri-modality (MRI/CT/PET) image fusion respectively. Inter-observer variation was assessed by the coefficient of variation (COV), the average distance between surface and centroid (ADSC), and the local standard deviation (SDlocal). Analysis of COV was also performed to evaluate intra-observer volume variation. Results The inter-observer variation analysis showed that, the mean COV was 0.14(±0.09) and 0.07(±0.01) for dual-modality and tri-modality respectively; the standard deviation of ADSC was significantly reduced (p<0.05) with tri-modality; SDlocal averaged over median GTV surface was reduced in patient 2 (from 0.57 cm to 0.39 cm) and patient 3 (from 0.42 cm to 0.36 cm) with the new method. The intra-observer volume variation was also significantly reduced (p = 0.00) with the tri-modality method as compared with using the dual-modality method. Conclusion With the new tri-modality image fusion method smaller inter- and intra-observer variation in GTV definition for the brain tumors can be achieved, which improves the consistency and accuracy for target delineation in individualized radiotherapy

Improved Efficiency of Perovskite Light-Emitting Diodes Using a Three-Step Spin-Coated CH3NH3PbBr3 Emitter and a PEDOT:PSS/MoO3-Ammonia Composite Hole Transport Layer

High efficiency perovskite light-emitting diodes (PeLEDs) using PEDOT:PSS/MoO3-ammonia composite hole transport layers (HTLs) with different MoO3-ammonia ratios were prepared and characterized. For PeLEDs with one-step spin-coated CH3NH3PbBr3 emitter, an optimal MoO3-ammonia volume ratio (0.02) in PEDOT:PSS/MoO3-ammonia composite HTL presented a maximum luminance of 1082 cd/m2 and maximum current efficiency of 0.7 cd/A, which are 82% and 94% higher than those of the control device using pure PEDOT:PSS HTL respectively. It can be explained by that the optimized amount of MoO3-ammonia in the composite HTLs cannot only facilitate hole injection into CH3NH3PbBr3 through reducing the contact barrier, but also suppress the exciton quenching at the HTL/CH3NH3PbBr3 interface. Three-step spin coating method was further used to obtain uniform and dense CH3NH3PbBr3 films, which lead to a maximum luminance of 5044 cd/m2 and maximum current efficiency of 3.12 cd/A, showing enhancement of 750% and 767% compared with the control device respectively. The significantly improved efficiency of PeLEDs using three-step spin-coated CH3NH3PbBr3 film and an optimum PEDOT:PSS/MoO3-ammonia composite HTL can be explained by the enhanced carrier recombination through better hole injection and film morphology optimization, as well as the reduced exciton quenching at HTL/CH3NH3PbBr3 interface. These results present a promising strategy for the device engineering of high efficiency PeLEDs

Effects of Charge Transport Materials on Blue Fluorescent Organic Light-Emitting Diodes with a Host-Dopant System

High efficiency blue fluorescent organic light-emitting diodes (OLEDs), based on 1,3-bis(carbazol-9-yl)benzene (mCP) doped with 4,4’-bis(9-ethyl-3-carbazovinylene)-1,1’-biphenyl (BCzVBi), were fabricated using four different hole transport layers (HTLs) and two different electron transport layers (ETLs). Fixing the electron transport material TPBi, four hole transport materials, including 1,1-Bis[(di-4-tolylamino)phenyl]cyclohexane (TAPC), N,N’-Di(1-naphthyl)-N,N’-diphenyl-(1,1’-biphenyl)-4’-diamine(NPB), 4,4’-Bis(N-carbazolyl)-1,1,-biphenyl (CBP) and molybdenum trioxide (MoO3), were selected to be HTLs, and the blue OLED with TAPC HTL exhibited a maximum luminance of 2955 cd/m2 and current efficiency (CE) of 5.75 cd/A at 50 mA/cm2, which are 68% and 62% higher, respectively, than those of the minimum values found in the device with MoO3 HTL. Fixing the hole transport material TAPC, the replacement of TPBi ETL with Bphen ETL can further improve the performance of the device, in which the maximum luminance can reach 3640 cd/m2 at 50 mA/cm2, which is 23% higher than that of the TPBi device. Furthermore, the lifetime of the device is also optimized by the change of ETL. These results indicate that the carrier mobility of transport materials and energy level alignment of different functional layers play important roles in the performance of the blue OLEDs. The findings suggest that selecting well-matched electron and hole transport materials is essential and beneficial for the device engineering of high-efficiency blue OLEDs

A new assessment model for tumor heterogeneity analysis with [18]F-FDG PET images

It has been shown that the intratumor heterogeneity can be characterized with quantitative analysis of the [18]F-FDG PET image data. The existing models employ multiple parameters for feature extraction which makes it difficult to implement in clinical settings for the quantitative characterization. This article reports an easy-to-use and differential SUV based model for quantitative assessment of the intratumor heterogeneity from 3D [18]F-FDG PET image data. An H index is defined to assess tumor heterogeneity by summing voxel-wise distribution of differential SUV from the [18]F-FDG PET image data. The summation is weighted by the distance of SUV difference among neighboring voxels from the center of the tumor and can thus yield increased values for tumors with peripheral sub-regions of high SUV that often serves as an indicator of augmented malignancy. Furthermore, the sign of H index is used to differentiate the rate of change for volume averaged SUV from its center to periphery. The new model with the H index has been compared with a widely-used model of gray level co-occurrence matrix (GLCM) for image texture characterization with phantoms of different configurations and the [18]F-FDG PET image data of 6 lung cancer patients to evaluate its effectiveness and feasibility for clinical uses. The comparison of the H index and GLCM parameters with the phantoms demonstrate that the H index can characterize the SUV heterogeneity in all of 6 2D phantoms while only 1 GLCM parameter can do for 1 and fail to differentiate for other 2D phantoms. For the 8 3D phantoms, the H index can clearly differentiate all of them while the 4 GLCM parameters provide complicated patterns in the characterization. Feasibility study with the PET image data from 6 lung cancer patients show that the H index provides an effective single-parameter metric to characterize tumor heterogeneity in terms of the local SUV variation, and it has higher correlation with tumor volume change after radiotherapy (R2 = 0.83) than the 4 GLCM parameters (R2 = 0.63, 0.73, 0.59 and 0.75 for Energy, Contrast, Local Homogeneity and Entropy respectively). The new model of the H index has the capacity to characterize the intratumor heterogeneity feature from 3D [18]F-FDG PET image data. As a single parameter with an intuitive definition, the H index offers potential for clinical applications

Automatic quantitative analysis of morphology of apoptotic HL-60 cells

Morphological identification is a widespread procedure to assess the presence of apoptosis by visual inspection of the morphological characteristics or the fluorescence images. The procedure is lengthy and results are observer dependent. A quantitative automatic analysis is objective and would greatly help the routine work. We developed an image processing and segmentation method which combined the Otsu thresholding and morphological operators for apoptosis study. An automatic determination method of apoptotic stages of HL-60 cells with fluorescence images was developed. Comparison was made between normal cells, early apoptotic cells and late apoptotic cells about their geometric parameters which were defined to describe the features of cell morphology. The results demonstrated that the parameters we chose are very representative of the morphological characteristics of apoptotic cells. Significant differences exist between the cells in different stages, and automatic quantification of the differences can be achieved