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OBJECTIVE: The aim of this study is to investigate the radiation dose and image quality of head CT using SPS and OBTCM techniques. METHODS: Three anthropomorphic head phantoms (1-yr-old, 5-yr-old, and adult) were used. Images were acquired using four modes (Default protocol, OBTCM, SPS, and SPS+OBTCM). Absorbed dose to the lens, anterior brain (brain_A), and posterior brain (brain_P) was measured and compared. Image noise and CNR were assessed in the selected regions of interest (ROIs). RESULTS: Compared with that in the Default protocol, the absorbed dose to the lens reduced by up to 28.33%,71.38%, and 71.12% in OBTCM, SPS, and SPS+OBTCM, respectively. The noise level in OBTCM slightly (≤1.45HU) increased than that in Default protocol, and the SPS or SPS+OBTCM mode resulted in a quantitatively small increase (≤2.58HU) in three phantoms. There was no significant difference in CNR of different phantoms under varies scanning modes (p > 0.05). CONCLUSIONS: During head CT examinations, the SPS mode can reduce the radiation dose while maintaining image quality. SPS+OBTCM couldn’t further effectively reduce the absorbed dose to the lens for 1-yr and 5-yr-old phantoms. Thus, SPS mode in pediatric and SPS+OBTCM mode in adult are better than other modes, and should be used in clinical practice.

The aim of this study was to investigate the impact of integrated parallel acquisition technology (iPAT) on the robustness of magnetic resonance imaging radiomic features.A phantom and 6 healthy volunteers were scanned on a clinical 3-T system using T1-weighted (S1), T1-weighted fluid-attenuated (S2), T2-weighted fluid-attenuated (S3), and T2-weighted (S4); 2 iPAT flavors (generalized autocalibration partially parallel acquisitions and modified sensitivity encoding [mSENSE]) and their different acceleration factors R. Radiomic features were extracted, and their robustness was assessed using coefficient of variation (CV), and differences between sequences and region of interest (ROI) were evaluated using the χ2 test.One volunteer was excluded because of movement during imaging acquisition. Generalized autocalibration partially parallel acquisitions provided more radiomic features with excellent robustness than mSENSE. Radiomic features with excellent robustness, unaffected by iPAT across different sequences and ROIs, in 92 radiomic features for phantom and healthy volunteers are 6.5% and 2.2%. For phantom, difference in the robustness degree between 4 sequences/P-ROIs was significant according to χ2 test; S2 and S3 could provide more excellent robust radiomic features than S1 and S4, and P-ROI3 filled with the biggest polystyrene particles could provide the most radiomic features with excellent robustness than the other P-ROIs. For healthy volunteers, only the difference in the degree of robustness between the 4 V-ROIs was significant, and V-ROI3 in white matter region of the left frontal lobe, which was located at periphery in image, could provide the most robust radiomic features compared with other V-ROIs.Integrated parallel acquisition technology had a significant impact on the robustness of radiomic features. Generalized autocalibration partially parallel acquisitions delivered a more robust substrate for radiomic analyses than mSENSE.

As an off-road racing car, driving conditions for a Baja racing car are particularly complex. Extreme working conditions such as deep pits and rocky roads have put higher demand on structural strength and frame safety. To solve this problem, extreme working conditions are first studied to check the safety of the steel tube frame of Baja racing cars. Secondly, based on Noise, Vibration, and Harshness (NVH) to explore the frame's characteristics, analyze the frame's six-order mode, make the corresponding optimization, and solve the resonance problem caused by engine excitation and other factors. Finally, the natural frequency of the frame is measured to verify the effectiveness of the NVH characteristic optimization results, and it is found that the experimental results match the theoretical values. The theoretical analysis results are mainly based on ANSYS software's static and modal analysis. Through the above steps, a set of finite element analyses and structural optimization schemes of AWD full-time four-wheel drive Baja racing car frame is systematically proposed, which has reference significance for the subsequent frame design.

The first postsynthetic solution-based crystal transformation of two-dimensional metal halide perovskites (2D MHPs) through organothiol-based reactions is reported. It is well-established that the ...

Transplantation of neural stem cells (NSCs) has been proved to promote functional rehabilitation of brain lesions including ischemic stroke. However, the therapeutic effects of NSC transplantation is limited by the low survival and differentiation rates of NSCs due to the harsh environment in the brain after ischemic stroke. Here, we employed NSCs derived from human induced pluripotent stem cells (iPSCs) together with exosomes extracted from NSCs to treat cerebral ischemia induced by middle cerebral artery occlusion/reperfusion (MCAO/R) in mice. The results showed that NSC-derived exosomes significantly reduced the inflammatory response, alleviated oxidative stress after NSC transplantation, and facilitated NSCs differentiationin vivo. The combination of NSCs with exosomes ameliorated the injury of brain tissue including cerebral infarct, neuronal death and glial scarring, and promoted the motor function recovery. To explore the underlying mechanisms, we analyzed the miRNA profiles of NSC-derived exosomes and the potential downstream genes. Our study provided the rationale for the clinical application of NSC-derived exosomes as a supportive adjuvant for NSC transplantation after stroke.

To develop a combined radiomics nomogram based on computed tomography (CT) images and clinical features to preoperatively distinguish Lauren's diffuse-type gastric cancer (GC) from intestinal-type GC.Ninety-five patients with Lauren's intestinal or diffuse-type GC confirmed by postoperative pathology had their preoperative clinical information and dynamic contrast CT images retrospectively analyzed and were subdivided into training and test groups in a 7:3 ratio. To select the optimal features and construct the radiomic signatures, we extracted, filtered, and minimized the radiomic features from arterial phase (AP) and venous phase (VP) CT images. We constructed four models (clinical model, AP radiomics model, VP radiomics model, and radiomics-clinical model) to assess and compare their predictive performance between the intestinal- and diffuse-type GC. Receiver-operating characteristic (ROC) curve, area under the ROC curve (AUC), and the DeLong test were used for assessment and comparison. In this study, radiomic nomograms integrating combined radiomic signatures and clinical characteristics were developed.Compared to the AP radiomics model, the VP radiomics model had better performance, with an AUC of 0.832 (95% confidence interval [CI], 0.735, 0.929) in the training cohort and 0.760 (95% CI 0.580, 0.940) in the test cohort. Among the combined models that assessed Lauren's type GC, the model including age and VP radiomics showed the best performance, with an AUC of 0.849 (95% CI 0.758, 0.940) in the training cohort and 0.793 (95% CI 0.629, 0.957) in the test cohort.Nomogram incorporating radiomic signatures and clinical features effectively differentiated Lauren's diffuse-type from intestinal-type GC.

Objective: To shorten acquisition time of readout segmentation of long variable echo trains (RESOLVE)-based diffusion kurtosis imaging (DKI) via Readout Partial Fourier (RPF) and b-value combinations. Methods: The RESOLVE-based DKI images of 38 patients with nasopharyngeal carcinoma (NPC) were prospectively enrolled. For RESOLVE-based DKI images with 5/8 RPF and without RPF, objective and subjective evaluations of image quality were performed. A total of nine groups with different b-value combinations were simulated, and the influence of different b-value combinations for RESOLVE-RPF-based DKI sequences was assessed using the intraclass correlation coefficient (ICC). Results: The mean values of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in DKI images without RPF were higher than those with 5/8 RPF (252.9 ± 77.7 vs 247.3 ± 85.5 and 5.8 ± 2.8 vs 5.4 ± 2.3, respectively), but not significantly (p = 0.460 and p = 0.180, respectively). In comparing the ICCs between nine groups of different b-value combinations in RESOLVE-RPF-based DKI, group (200, 800, 2000 s/mm2), group (200, 400, 800, 2000 s/mm2) and group (200, 800, 1500, 2000 s/mm2) were not significantly different (p > 0.001) and showed excellent agreement (0.81–1.00) with that of group (200, 400, 800, 1500, 2000 s/mm2). Using b-value optimization and RPF technology, the group with RPF (200, 400, 800, 2000 s/mm2) showed a 56% reduced scanning compared with the group without RPF (200, 400, 800, 1500, 2000 s/mm2; 3 min 46 s vs 8 min 31 s, respectively). Conclusion: DKI with RPF did not significantly affect image quality, but both RPF and different b-value combinations can affect the scanning time. The combination of RPF and b-value optimization can ensure the stability of DKI parameters and reduce the scanning time by 56%. Advances in knowledge: This work is to optimize scan parameters, e.g. RPF and b-value combinations, to reduce acquisition time for RESOLVE-based DKI in NPC. To our knowledge, the effect of RESOLVE-RPF and b-value combinations on DKI has not been reported.

The mutation status of KRAS is a significant biomarker in the prognosis of rectal cancer. This study investigated the feasibility of MRI-based radiomics in predicting the mutation status of KRAS with a composite index which could be an important criterion for KRAS mutation in clinical practice. In this retrospective study, a total of 127 patients with rectal cancer were enrolled. The 3D Slicer was used to extract the radiomics features from the MRI images, and sparse support vector machine (SVM) with linear kernel was applied for feature reduction. The radiomics classifier for predicting the KRAS status was then constructed by Linear Discriminant Analysis (LDA) and its performance was evaluated. The composite index was determined with LDA model. Out of 127 rectal cancer subjects, there were 44 KRAS mutation cases and 83 wild cases. A total of 104 radiomics features were extracted, 54 features were filtered by linear SVM with L1-norm regularization and 6 features that had no significant correlations within them were finally selected. The radiomics classifier constructed using the 6 features featured an AUC value of 0.669 (specificity: 0.506; sensitivity: 0.773) with LDA. Furthermore, the composite index (Radscore) had statistically significant difference between the KRAS mutation and wild groups. It is suggested that the MRI-based radiomics has the potential in predicting the KRAS status in patients with rectal cancer, which may enhance the diagnostic value of MRI in rectal cancer.

Purpose The purpose of this study is to evaluate the feasibility of using deformable image registration algorithms to improve high-dose-rate high-risk clinical target volume (HR-CTV) delineation between preapplicator implantation MRI (pre-MRI) and postapplicator implantation CT (post-CT) in the treatment of locally advanced cervical cancer (LACC). Method and materials Twenty-six patients were identified for the study. Regions of interest were segmented on MRI and CT. A HR-CTV was delineated on pre-MRI and compared with the previously contoured HR-CTV on the post-CT. Two commercially available algorithms, ANACONDA (anatomically constrained) and MORFEUS (biomechanical model based) with various controlling structure settings, including the cervix, uterus, etc., were used to deform pre-MRI to post-CT. MRI-to-CT deformed targets are denoted as HR-CTV’. Quantitative deformation metrics include Dice index, distance to agreement, and center of mass displacement. Qualitative clinical usefulness of deformations was scored based on HR-CTV identification on CT images. Results For ANACONDA and MORFEUS deformations, using a cervix controlling region of interest resulted in the highest Dice, lowest distance to agreement, and lowest center of mass displacement for HR-CTV′. With MORFEUS deformations, the deformed HR-CTV’ proved clinically useful in 23 patients. Conclusions Prebrachytherapy implantation MRI can aid target contours for CT-based brachytherapy through ANACONDA or MORFEUS algorithms with appropriate parameter selection for LACC patients.

Author(s): Yuan, Zilong; Rong, Yi; Benedict, Stanley H; Daly, Megan E; Qiu, Jianfeng; Yamamoto, Tokihiro | Abstract: PURPOSE:Adaptive radiotherapy (ART) has potential to reduce toxicity and facilitate safe dose escalation. Dose calculations with the planning CT deformed to cone beam CT (CBCT) have shown promise for estimating the "dose of the day". The purpose of this study is to investigate the "dose of the day" calculation accuracy based on CBCT and deformable image registration (DIR) for lung cancer radiotherapy. METHODS:A total of 12 lung cancer patients were identified, for which daily CBCT imaging was performed for treatment positioning. A re-planning CT (rCT) was acquired after 20nGy for all patients. A virtual CT (vCT) was created by deforming initial planning CT (pCT) to the simulated CBCT that was generated from deforming CBCT to rCT acquired on the same day. Treatment beams from the initial plan were copied to the vCT and rCT for dose calculation. Dosimetric agreement between vCT-based and rCT-based accumulated doses was evaluated using the Bland-Altman analysis. RESULTS:Mean differences in dose-volume metrics between vCT and rCT were smaller than 1.5%, and most discrepancies fell within the range ofn±n5% for the target volume, lung, esophagus, and heart. For spinal cord Dmax , a large mean difference of -5.55% was observed, which was largely attributed to very limited CBCT image quality (e.g., truncation artifacts). CONCLUSION:This study demonstrated a reasonable agreement in dose-volume metrics between dose accumulation based on vCT and rCT, with the exception for cases with poor CBCT image quality. These findings suggest potential utility of vCT for providing a reasonable estimate of the "dose of the day", and thus facilitating the process of ART for lung cancer.

Yu Qian,1,2,* Yuan Wu,3,* Zilong Yuan,4 Xiaohui Niu,5 Yaoyao He,4 Jun Peng,6 Fuxiang Zhou,1 Shaozhong Wei,7 Desheng Hu,3 Yunfeng Zhou1 1Department of Radiation and Medical Oncology, Zhongnan Hospital, Wuhan University, Wuhan, Hubei, People’s Republic of China; 2Department of Medical Oncology, Hubei Cancer Hospital, Wuhan, Hubei, People’s Republic of China; 3Department of Radiation Oncology, Hubei Cancer Hospital, Wuhan, Hubei, People’s Republic of China; 4Department of Radiology, Hubei Cancer Hospital, Wuhan, Hubei, People’s Republic of China; 5College of Informatics, Huazhong Agricultural University, Wuhan, Hubei, People’s Republic of China; 6Department of Pathology, Hubei Cancer Hospital, Wuhan, Hubei, People’s Republic of China; 7Department of Surgery, Hubei Cancer Hospital, Wuhan, Hubei, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yunfeng ZhouDepartment of Radiation and Medical Oncology, Zhongnan Hospital, 169 Donghu Road, Wuhan, Hubei, People’s Republic of ChinaTel +86 139 0715 4247Fax +86 27 6781 2892Email yfzhouwhu@163.comDesheng HuDepartment of Radiation Oncology, Hubei Cancer Hospital, 16 Zhuodaoquan S Road, Wuhan, Hubei, People’s Republic of ChinaTel +86 27 8767 0318Fax +86 27 8767 0151Email hds13907174495@163.comPurpose: Circulating tumour cells (CTCs) have been found to correlate with treatment response and prognosis in some cancers; however, such correlations have not been reported in nasopharyngeal carcinoma (NPC). We aimed to determine the relationship between CTCs and the treatment response in NPC.Patients and methods: In this prospective study, we ascertained the karyotype of CTCs and identified a possible correlation between karyotype and treatment response in locally advanced NPC (LANPC). We prospectively collected peripheral blood from LANPC patients. CTCs were measured by negative enrichment with immunofluorescence in situ hybridization (imFISH) and a centromere of chromosome 8 (CEP8) probe. Chromosome 8 was karyotyped in CTCs, which were identified as triploid, tetraploid or multiploid. Patients were then treated with platinum-based induction chemotherapy followed by concurrent chemoradiotherapy. CTCs were measured before and after treatment.Results: We detected CTCs in 27 of 50 (54%) patients, which served as a baseline value. The results were independent of age, smoking history and NPC clinical stage. All of the 27 evaluable enrolled patients with detectable CTCs showed decreases in both total CTCs and CTCs of different ploidies after treatment (P

Purpose To identify factors associated with MRI-to-CT image deformation accuracy and modes of failure for MRI-optimized intracavitary high-dose-rate treatment of locally advanced cervical cancer. Methods and Materials Twenty-six patients with locally advanced cervical cancer had preimplantation MRI registered and deformed to postimplantation CT images using anatomically constrained and biomechanical model–based deformable image registration (DIR) algorithms. Cervix (primary) and cervix plus 10-mm margin (secondary) were used as controlling regions of interest for deformation. High-risk clinical target volume defined on pre-MRI was propagated to CT and evaluated for clinical utility in optimizing target volumes using scores 0 (low performing) to 4 (high performing). Quantitative evaluation of deformation performance included Dice index, distance to agreement, center of mass (COM) differences, cervical/uterus volume, and geometric change in organ position for MR-projected structures. Statistical analysis was performed to identify predictors of clinical utility and modes of failure. Results Anatomically constrained and biomechanical model–based deformable image registration algorithms achieved clinical utility >3 in 65% and 81% of patients, respectively. This improved to 81% and 85%, respectively, if cervix plus margin was used to drive deformations. Total COM displacement (cervix plus uterus) had the highest sensitivity in predicting low from high clinical utility in optimizing target volumes. Deformation failure (low clinical utility) resulted from high COM displacement, high cervical volume change, and retroverted uterine anatomy. Conclusions MRI-to-CT deformable image registration using a cervix-controlling region of interest can aid clinical target delineation in cervical brachytherapy and potentially improve brachytherapy implant quality and clinical workflow. Deformation failures warrant further study and prospective deformation validation.

BACKGROUND In glaucoma, the cup to plate ratio enlargement is a recognized pathological phenomenon. At present, the research on optic nerve in China and abroad mainly focuses on 2-dimensional research, and the measurement of 3-dimensional volume data is less well studied. Therefore, the recognition of 3-dimensional morphological changes is conducive to timely clinical intervention to prevent or slow down progressive vision loss. MATERIAL AND METHODS In this paper, optical coherence tomography (OCT) volume imaging technology was used to analyze and compare the morphological changes of primary acute angle-closure glaucoma in three-dimensional morphology, reconstruct the volume data of three-dimensional optic nerve head (ONH), and make morphological measurements. RESULTS The rim width of the glaucoma group was significantly lower than that of the control group, and the average volume and intraocular pressure of the optic cup were significantly increased (P0.05), while the rim width and intraocular pressure of the other group were not significantly changed (P0.05). CONCLUSIONS We used three-dimensional reconstruction to identify OCT images between glaucoma patients and the control group with significant differences.

Objective For locally advanced nasopharyngeal carcinoma (LA-NPC) patients, high incidences of distant metastases and severe treatment related toxicities are the main obstacles needed to be overcome. Raltitrexed, a specific thymidylate synthase inhibitor with a convenient administration schedule, has an acceptable and manageable toxicity, and possesses radio-sensitizing properties. To investigate the efficacy and safety of raltitrexed and cisplatin induction chemotherapy and concurrent chemoradiotherapy (IC+CCRT) in patients with LA-NPC, a phase II clinical study was conducted. Methods Sixty eligible patients with LA-NPC were enrolled into this study. A raltitrexed-cisplatin combination was used as part of an IC+CCRT regimen. Raltitrexed-cisplatin IC was given once every 3 weeks (q3w) for two cycles, followed by raltitrexed-cisplatin based CCRT q3w for two cycles. Intensity-modulated radiotherapy (IMRT) was given for all enrolled patients. Results All patients were included in survival analysis according to the intent-to-treat principle. The objective response rate (ORR) 3 months after treatment was 98%. The 2-year overall survival (OS) rate was 92%. The median relapse-free survival (RFS) time was 30.5 [95% confidence interval (95% CI), 28.4-32.3] months. The 2-year RFS rate was 85%. The 2-year local failure-free survival (LFFS) rate was 97% and the 2-year distant metastasis-free survival (DMFS) rate was 88%. Acute toxicities were mostly grade 2 and 3 reactions in bone marrow suppression, gastrointestinal side effect and oropharyngeal mucositis. Only two patients occurred grade 4 acute toxicities, one was bone marrow suppression and the other was dermatitis radiation. Conclusions The combination of raltitrexed and cisplatin has a comparable efficacy to those in standard first-line therapy.

Objective. Brain age, which is predicted using neuroimaging data, has become an important biomarker in aging research. This study applied diffusion tensor imaging (DTI) and generalized q-sampling imaging (GQI) model to predict age respectively, with the purpose of evaluating which diffusion model is more accurate in estimating age and revealing age-related changes in the brain. Approach. Diffusion MRI data of 125 subjects from two sites were collected. Fractional anisotropy (FA) and quantitative anisotropy (QA) from the two diffusion models were calculated and were used as features of machine learning models. Sequential backward elimination algorithm was used for feature selection. Six machine learning approaches including linear regression, ridge regression, support vector regression (SVR) with linear kernel, quadratic kernel and radial basis function (RBF) kernel and feedforward neural network were used to predict age using FA and QA features respectively. Main results. Age predictions using FA features were more accurate than predictions using QA features for all the six machine learning algorithms. Post-hoc analysis revealed that FA was more sensitive to age-related white matter alterations in the brain. In addition, SVR with RBF kernel based on FA features achieved better performances than the competing algorithms with mean absolute error ranging from 7.74 to 10.54, mean square error (MSE) ranging from 87.79 to 150.86, and normalized MSE ranging from 0.05 to 0.14. Significance. FA from DTI model was more suitable than QA from GQI model in age prediction. FA metric was more sensitive to age-related white matter changes in the brain and FA of several brain regions could be used as white matter biomarkers in aging.

Background The reproducibility of intravoxel incoherent motion (IVIM)-based radiomics studies in humans has not been reported. Purpose To determine the inter- and intra-observer variability on the reproducibility of IVIM-based radiomics features in cervical cancer (CC). Material and Methods The IVIM images of 25 patients with CC were retrospectively collected. Based on the high-resolution T2-weighted images, the regions of interest (ROIs) were independently delineated twice in diffusion-weighted images at a b value of 1000 s/mm2 (interval time was one month) by two radiologists. This was done at the largest transversal cross-sections of the tumors. The ROI was subsequently used in apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) maps derived from IVIM images. In total, 105 radiomics features were then finally extracted from the IVIM-derived maps. The inter- and intra-observer reproducibility of IVIM-derived features was then evaluated using the intraclass correlation coefficient. Results Inter- and intra-observer variability affected the reproducibility of radiomics features. D* map had 100% and 95% reproducible features, ADC map had 89% and 93%, D map had 97% and 86%, while f map had 54% and 62% reproducible features with good to excellent reliability in the intra-observer analysis. Similarly, D* map had 90% and 94%, ADC map had 85% and 70%, D map had 81% and 78%, while f map had 41% and 93% reproducible features with good to excellent reliability in the inter-observer analysis. Conclusion Inter- and intra-observer variability can affect radiomics analysis. Cognizant to this, multicenter studies should pay more attention to intra- and inter-observer variability.

Based on Magnetic Resonance Imaging, Magnetic Resonance Electrical Properties Tomography is a promising means to reveal the conductivity and permittivity distributions of biological tissue, without any additional electrodes or coils. The benefit of the Magnetic Resonance Electrical Properties Tomography was that the tumor lesion could be distinguished early than the changes happened in the structure. Many studies have been done in the field of the inversion algorithms to process the radio frequency magnetic field. The radio frequency magnetic field mapping is the foundation of the Magnetic Resonance Electrical Properties Tomography. The tissue electrical properties control the behavior of magnetic field, which can be measured by MRI scanning. In the paper, the target application of the tomography is clinical nasopharyngeal carcinoma screening. With a 3 Tesla MRI scanner, the radio frequency magnetic field mapping was carried. The field of view was 239 × 209 mm2 with the longitudinal dimension of 120 mm. A Longitudinal-relaxation-time turbo-spin-echo imaging was implemented as a reference of the lesion. Base on the Helmholtz equation, which assuming the distribution of electrical properties smooth, the conductivity and permittivity images were reconstructed. The image by the longitudinal relaxation time turbo spin echo sequence presented a proof of the position of the Nasopharyngeal Carcinoma lesion. From the two resultant properties images, the anatomical structure was acceptable, but the lesion region could not be recognized due to the algorithm itself. A gradient-model algorithm is in progress to solve the problem for potential medicine applications.

BACKGROUND Generalized q-sampling (GQI) and connectometry analysis provide new indices, i.e., quantitative anisotropy (QA) and spin distribution function (SDF) in comparison with diffusion tensor imaging (DTI). They may provide more age-related changes in white matter (WM) in aging. PURPOSE To investigate the feasibility of using GQI and connectometry analysis to determine WM properties changes in aging. STUDY TYPE Cross-cohort research. POPULATION Fifty normal adults (27 females) aged 21-71 years. FIELD STRENGTH/SEQUENCE T1 -weighted images (T1 WI) and high angular resolution diffusion imaging (HARDI) images were acquired at 1.5T. ASSESSMENT HARDI data were analyzed using DTI and GQI to obtain fractional anisotropy (FA), QA, fiber numbers, and fiber lengths for tract analysis and using q-space diffeomorphic reconstruction (QSDR) for the connectometry analysis. We compared differences of DTI, GQI, and connectometry analysis to reflect WM changes in aging. STATISTICAL TESTS Associations between FA, QA, and fiber numbers and lengths and age were analyzed using Pearson's correlation coefficients. The connectometry analysis was conducted using a multiple linear regression analysis, including age and gender as factors. Uncorrected P-value/false discovery rate (FDR) (corrected for multiple comparisons) 6 regions, P 7 regions, P < 0.05). However, DTI and GQI analyses revealed consistent results in some regions, including the genu of the corpus callosum (GCC), body of the corpus callosum (BCC), fornix (Fx), and anterior coronal radiation (ACR) (P < 0.05). The connectometry analysis showed more tract changes associated with age at an FDR of 0.05, which partially overlapped with the FA and QA. DATA CONCLUSION GQI and connectometry provide more information about age-related tracts and complement the DTI findings. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2018;48:369-381.

The Bayesian neural network approach has been employed to improve the nuclear magnetic moment predictions of odd-A nuclei. The Schmidt magnetic moment obtained from the extreme single-particle shell model makes large root-mean-square (rms) deviations from data, i.e., 0.949 and 1.272 for odd-neutron nuclei and odd-proton nuclei, respectively. By including the dependence of the nuclear spin and Schmidt magnetic moment, the machine-learning approach precisely describes the magnetic moments of odd-A nuclei with rms deviations of 0.036 for odd-neutron nuclei and 0.061 for odd-proton nuclei. Furthermore, the evolution of magnetic moments along isotopic chains, including the staggering and sudden jump trend, which are difficult to describe using nuclear models, have been well reproduced by the Bayesian neural network (BNN) approach. The magnetic moments of doubly closed-shell nuclei, for example, isoscalar and isovector magnetic moments, have been well studied and compared with the corresponding non-relativistic and relativistic calculations.

Background The impact of variable b-value combinations on apparent diffusion coefficient (ADC)-based radiomics features has not been fully addressed in literature. Purpose To investigate the correlation between radiomics features extracted from ADC maps and various b-value combinations in cervical cancer. Material and Methods Diffusion-weighted images (b-values: 0, 600, 800, and 1000 s/mm2) of 20 patients with cervical cancer were included. Tumors were identified with the largest transversal cross-section and manually segmented by radiologist. For each b-value combination, 92 radiomics features were extracted and coefficient of variance (CV) was used to evaluate the robustness of radiomics features with different b-value combinations. Features with CV > 5% were normalized by the mean feature variation across the group. Results Out of a total of 92 radiomics features, 18 were classified as robust features with CV ≤5%. Among the rest (CV > 5%), 11, 23, and 40 features demonstrated 5%< CV ≤10%, 10%< CV ≤20%, and CV > 20%, respectively. A subset of features in each category (CV > 5%) showed strong correlation with the b-value combination variation, including 44% (7/16) features in gray level co-occurrence matrix, 62% (8/13) features in gray level dependence matrix, 64% (9/14) features in first order, 50% (8/16) features in gray level run length matrix, 57% (8/14) features in gray level size matrix, and 20% (1/5) features in neighborhood gray-tone difference matrix. Conclusions Variations in b-value combinations demonstrated impact on radiomics features extracted from ADC maps for cervical cancer. The radiomics features with CV

Background This retrospective study was undertaken to determine if the plasma circulating tumor DNA (ctDNA) level and tumor biological features in patients with advanced solid tumors affected the detection of genomic alterations (GAs) by a plasma ctDNA assay. Method Cell-free DNA (cfDNA) extracted from frozen plasma (N = 35) or fresh whole blood (N = 90) samples were subjected to a 62-gene hybrid capture-based next-generation sequencing assay FoundationACT. Concordance was analyzed for 51 matched FoundationACT and FoundationOne (tissue) cases. The maximum somatic allele frequency (MSAF) was used to estimate the amount of tumor fraction of cfDNA in each sample. The detection of GAs was correlated with the amount of cfDNA, MSAF, total tumor anatomic burden (dimensional sum), and total tumor metabolic burden (SUVmax sum) of the largest ten tumor lesions on PET/CT scans. Results FoundationACT detected GAs in 69 of 81 (85%) cases with MSAF > 0. Forty-two of 51 (82%) cases had ≥ 1 concordance GAs matched with FoundationOne, and 22 (52%) matched to the National Comprehensive Cancer Network (NCCN)-recommended molecular targets. FoundationACT also detected 8 unique molecular targets, which changed the therapy in 7 (88%) patients who did not have tumor rebiopsy or sufficient tumor DNA for genomic profiling assay. In all samples (N = 81), GAs were detected in plasma cfDNA from cancer patients with high MSAF quantity (P = 0.0006) or high tumor metabolic burden (P = 0.0006) regardless of cfDNA quantity (P = 0.2362). Conclusion This study supports the utility of using plasma-based genomic assays in cancer patients with high plasma MSAF level or high tumor metabolic burden.

Under the duplex framework of the rapid transformation of the conventional power grid to the energy Internet and the swift development of network attack technologies, the security and protection of the energy Internet are becoming increasingly precarious. The energy Internet attack prediction method has become a current research hotspot. The current research in this area is predominantly focused on security to protect and reduce losses, it is impossible to counter the attacks faced by the Energy Internet promptly, and there is a lack of online predictive security analysis methods and tools. Aiming at the shortcomings of traditional research and the current stage, this paper proposes an online prediction and analysis method of energy Internet security situation based on the combination of temporal convolutional neural network (TCN) and gated recurrent neural network (LSTM). This method which based on the security status data set can predict and analyse the region Energy Internet security, and the mean absolute error and mean squared error are 0.352 and 0.2714 respectively. The results show that the prediction performance of the algorithm has been improved, the stability is robust, and it can be applied to the energy Internet security situation prediction.

Cerebral structures in both cortical and subcortical regions change with aging. More specific and comprehensive studies are needed to better elucidate these changes.To investigate the relationships between age and cerebral structures regarding cortical and subcortical changes.Cross-cohort research.54 healthy adults (28 females) aged 21-71 years.TThe cortical thickness, local gyrification index (LGI), and the volumes of total gray matter (GM), white matter (WM), white matter hyperintensity (WMH), deep gray matter nuclei (putamen, pallidum, thalamus, caudate, amygdala, accumbens area, and hippocampus), ventricles, and hippocampal subfields were obtained using FreeSurfer software.Regression analysis was performed to determine the relationships between age and cortical thickness, LGI, and volumes of subcortical structures. Uncorrected P values ≤ 0.001 and RThe cortical thickness and LGI decreased with age throughout almost all brain regions (RThe results comprehensively show the relationships between age and cerebral structures in multiple brain regions, and these findings may help identify normal aging and other age-related neuroradiological disorders.2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:152-163.

This work evaluated a commercial fallback planning workflow designed to provide cross-platform treatment planning and delivery. A total of 27 helical tomotherapy intensity-modulated radiotherapy plans covering 4 anatomical sites were selected, including 7 brain, 5 unilateral head and neck, 5 bilateral head and neck, 5 pelvis, and 5 prostate cases. All helical tomotherapy plans were converted to 7-field/9-field intensity-modulated radiotherapy and volumetric-modulated radiotherapy plans through fallback dose-mimicking algorithm using a 6-MV beam model. The planning target volume (PTV) coverage ( D1, D99, and homogeneity index) and organs at risk dose constraints were evaluated and compared. Overall, all 3 techniques resulted in relatively inferior target dose coverage compared to helical tomotherapy plans, with higher homogeneity index and maximum dose. The organs at risk dose ratio of fallback to helical tomotherapy plans covered a wide spectrum, from 0.87 to 1.11 on average for all sites, with fallback plans being superior for brain, pelvis, and prostate sites. The quality of fallback plans depends on the delivery technique, field numbers, and angles, as well as user selection of structures for organs at risk. In actual clinical scenario, fallback plans would typically be needed for 1 to 5 fractions of a treatment course in the event of machine breakdown. Our results suggested that

Generalized q-sampling (GQI) and connectometry analysis provide new indices, i.e., quantitative anisotropy (QA) and spin distribution function (SDF) in comparison with diffusion tensor imaging (DTI). They may provide more age-related changes in white matter (WM) in aging.To investigate the feasibility of using GQI and connectometry analysis to determine WM properties changes in aging.Cross-cohort research.Fifty normal adults (27 females) aged 21-71 years.THARDI data were analyzed using DTI and GQI to obtain fractional anisotropy (FA), QA, fiber numbers, and fiber lengths for tract analysis and using q-space diffeomorphic reconstruction (QSDR) for the connectometry analysis. We compared differences of DTI, GQI, and connectometry analysis to reflect WM changes in aging.Associations between FA, QA, and fiber numbers and lengths and age were analyzed using Pearson's correlation coefficients. The connectometry analysis was conducted using a multiple linear regression analysis, including age and gender as factors. Uncorrected P-value/false discovery rate (FDR) (corrected for multiple comparisons)0.05 was considered statistically significant.More regional changes were detected in FA related to age than changes in QA (176 regions, P0.05). Fewer regional changes in fiber numbers and more changes of fiber lengths were observed for DTI than for GQI (58/107 regions, P0.05). However, DTI and GQI analyses revealed consistent results in some regions, including the genu of the corpus callosum (GCC), body of the corpus callosum (BCC), fornix (Fx), and anterior coronal radiation (ACR) (P0.05). The connectometry analysis showed more tract changes associated with age at an FDR of 0.05, which partially overlapped with the FA and QA.GQI and connectometry provide more information about age-related tracts and complement the DTI findings.2 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2018;48:369-381.

Routine follow-up visits and radiographic imaging are required for outcome evaluation and tumor recurrence monitoring. Yet more personalized surveillance is required in order to sufficiently address the nature of heterogeneity in nonsmall cell lung cancer and possible recurrences upon completion of treatment. Radiomics, an emerging noninvasive technology using medical imaging analysis and data mining methodology, has been adopted to the area of cancer diagnostics in recent years. Its potential application in response assessment for cancer treatment has also drawn considerable attention. Radiomics seeks to extract a large amount of valuable information from patients' medical images (both pretreatment and follow-up images) and quantitatively correlate image features with diagnostic and therapeutic outcomes. Radiomics relies on computers to identify and analyze vast amounts of quantitative image features that were previously overlooked, unmanageable, or failed to be identified (and recorded) by human eyes. The research area has been focusing on the predictive accuracy of pretreatment features for outcome and response and the early discovery of signs of tumor response, recurrence, distant metastasis, radiation-induced lung injury, death, and other outcomes, respectively. This review summarized the application of radiomics in response assessments in radiotherapy and chemotherapy for non-small cell lung cancer, including image acquisition/reconstruction, region of interest definition/segmentation, feature extraction, and feature selection and classification. The literature search for references of this article includes PubMed peer-reviewed publications over the last 10 years on the topics of radiomics, textural features, radiotherapy, chemotherapy, lung cancer, and response assessment. Summary tables of radiomics in response assessment and treatment outcome prediction in radiation oncology have been developed based on the comprehensive review of the literature.

e17523 Background: Circulating tumor cells (CTCs) have been showed to correlate with curative effects and prognosis in many cancers, but there are few data describing the importance of CTCs in nasopharyngeal carcinoma (NPC). Our aim was to prospect the karyotyping of CTCs and the correlation between CTCs and clinical response in patients with locally advanced NPC. Methods: Serum was collected in 82 patients with locally advanced NPC. CTC was measured by negative enrichment with immunostaining of CD45, DAPI and imFISH with the centromere of chromosome 8 probe (CEP8) method. Cells with CD45-/DAPI+/CEP8 ≥3 were defined as positive CTCs and the karyotyping of chromosome 8 in CTCs were identified as triploidy, tetraploidy and multiploidy. Patients were treated with 2 cycles of induction chemotherapy followed by concurrent chemoradiotherapy according to the clinical trial (NCT 02562599). CTC was also measured after each cycle of chemotherapy. Clinial response was classified according to the Response Evaluation Criteria in Solid Tumours (RECIST 1.1) criteria. Results: Positive CTCs were detected in 42 of 82 patients prior to treatment. They were independent with age, sex, smoking and clinical stages. Continuous CTC detection of 30 enrolled patients with positive CTCs showed that the ratio of CTCs and CTCs with different ploidies significantly decreased after therapy (P < 0.05). Although the change was not correlated with clinical response (P = 0.054), the decreases in CTCs count of patients who had complete response (CR) to the treatment were significant (P < 0.05), while the decreases of CTCs count of patients who had partial response (PR) were not (P > 0.05). Further analysis indicated that CR patients had fewer tetraploidy CTCs prior to the therapy than PR patients (P < 0.05). Moreover, tetraploidy CTCs count also indicated a positive prediction value for clinical response to treatment according to maximum likelihood estimation (P = 0.045, 95%CI [1.032,18.060]). Conclusions: The decrease of CTCs is correlated with a better therapeutic efficacy in patients with locally advanced NPC and the number of tetraploidy CTCs before treatment could be used as a predictive factor for clinical outcomes.