Image quality characterization of an ultra-high-speed kilovoltage cone-beam computed tomography imaging system on an O-ring linear accelerator

PURPOSE

The quality of on-board imaging systems, including cone-beam computed tomography (CBCT), plays a vital role in image-guided radiation therapy (IGRT) and adaptive radiotherapy. Recently, there has been an upgrade of the CBCT systems fused in the O-ring linear accelerators called HyperSight, featuring a high imaging performance. As the characterization of a new imaging system is essential, we evaluated the image quality of the HyperSight system by comparing it with Halcyon 3.0 CBCT and providing benchmark data for routine imaging quality assurance.

METHODS

The HyperSight features ultra-fast scan time, a larger kilovoltage (kV) detector, a more substantial kV tube, and an advanced reconstruction algorithm. Imaging protocols in the two modes of operation, treatment mode with IGRT and the CBCT for planning (CBCTp) mode were evaluated and compared with Halcyon 3.0 CBCT. Image quality metrics, including spatial resolution, contrast resolution, uniformity, noise, computed tomography (CT) number linearity, and calibration error, were assessed using a Catphan and an electron density phantom and analyzed with TotalQA software.

RESULTS

HyperSight demonstrated substantial improvements in contrast-to-noise ratio and noise in both IGRT and CBCTp modes compared to Halcyon 3.0 CBCT. CT number calibration error of HyperSight CBCTp mode (1.06%) closely matches that of a full CT scanner (0.72%), making it suitable for adaptive planning. In addition, the advanced hardware of HyperSight, such as ultra-fast scan time (5.9 s) or 2.5 times larger heat unit capacity, enhanced the clinical efficiency in our experience.

CONCLUSIONS

HyperSight represented a significant advancement in CBCT imaging. With its image quality, CT number accuracy, and ultra-fast scans, HyperSight has a potential to transform patient care and treatment outcomes. The enhanced scan speed and image quality of HyperSight are expected to significantly improve the quality and efficiency of treatment, particularly benefiting patients.

A quality assurance framework for routine monitoring of deep learning cardiac substructure computed tomography segmentation models in radiotherapy

BACKGROUND

For autosegmentation models, the data used to train the model (e.g., public datasets and/or vendor-collected data) and the data on which the model is deployed in the clinic are typically not the same, potentially impacting the performance of these models by a process called domain shift. Tools to routinely monitor and predict segmentation performance are needed for quality assurance. Here, we develop an approach to perform such monitoring and performance prediction for cardiac substructure segmentation.

PURPOSE

To develop a quality assurance (QA) framework for routine or continuous monitoring of domain shift and the performance of cardiac substructure autosegmentation algorithms.

METHODS

A benchmark dataset consisting of computed tomography (CT) images along with manual cardiac substructure delineations of 241 breast cancer radiotherapy patients were collected, including one "normal" image domain of clean images and five "abnormal" domains containing images with artifact (metal, contrast), pathology, or quality variations due to scanner protocol differences (field of view, noise, reconstruction kernel, and slice thickness). The QA framework consisted of an image domain shift detector which operated on the input CT images and a shape quality detector on the output of an autosegmentation model, and a regression model for predicting autosegmentation model performance. The image domain shift detector was composed of a trained denoising autoencoder (DAE) and two hand-engineered image quality features to detect normal versus abnormal domains in the input CT images. The shape quality detector was a variational autoencoder (VAE) trained to estimate the shape quality of the auto-segmentation results. The output from the image domain shift and shape quality detectors was used to train a regression model to predict the per-patient segmentation accuracy, measured by Dice coefficient similarity (DSC) to physician contours. Different regression techniques were investigated including linear regression, Bagging, Gaussian process regression, random forest, and gradient boost regression. Of the 241 patients, 60 were used to train the autosegmentation models, 120 for training the QA framework, and the remaining 61 for testing the QA framework. A total of 19 autosegmentation models were used to evaluate QA framework performance, including 18 convolutional neural network (CNN)-based and one transformer-based model.

RESULTS

When tested on the benchmark dataset, all abnormal domains resulted in a significant DSC decrease relative to the normal domain for CNN models (p < 0.001 $p < 0.001$ ), but only for some domains for the transformer model. No significant relationship was found between the performance of an autosegmentation model and scanner protocol parameters (p = 0.42 $p = 0.42$ ) except noise (p = 0.01 $p = 0.01$ ). CNN-based autosegmentation models demonstrated a decreased DSC ranging from 0.07 to 0.41 with added noise, while the transformer-based model was not significantly affected (ANOVA,p = 0.99 $p=0.99$ ). For the QA framework, linear regression models with bootstrap aggregation resulted in the highest mean absolute error (MAE) of0.041 ± 0.002 $0.041 \pm 0.002$ , in predicted DSC (relative to true DSC between autosegmentation and physician). MAE was lowest when combining both input (image) detectors and output (shape) detectors compared to output detectors alone.

CONCLUSIONS

A QA framework was able to predict cardiac substructure autosegmentation model performance for clinically anticipated "abnormal" domain shifts.

Millimeter wave-based patient setup verification and motion tracking during radiotherapy

BACKGROUND

Position verification and motion monitoring are critical for safe and precise radiotherapy (RT). Existing approaches to these tasks based on visible light or x-ray are suboptimal either because they cannot penetrate obstructions to the patient's skin or introduce additional radiation exposure. The low-cost mmWave radar is an ideal solution for these tasks as it can monitor patient position and motion continuously throughout the treatment delivery.

PURPOSE

To develop and validate frequency-modulated continuous wave (FMCW) mmWave radars for position verification and motion tracking during RT delivery.

METHODS

A 77 GHz FMCW mmWave module was used in this study. Chirp Z Transform-based (CZT) algorithm was developed to process the intermediate frequency (IF) signals. Absolute distances to flat Solid Water slabs and human shape phantoms were measured. The accuracy of absolute distance and relative displacement were evaluated.

RESULTS

Without obstruction, mmWave based on the CZT algorithm was able to detect absolute distance within 1 mm for a Solid Water slab that simulated the reflectivity of the human body. Through obstructive materials, the mmWave device was able to detect absolute distance within 5 mm in the worst case and within 3.5 mm in most cases. The CZT algorithm significantly improved the accuracy of absolute distance measurement compared with Fast Fourier Transform (FFT) algorithm and was able to achieve submillimeter displacement accuracy with and without obstructions. The surface-to-skin distance (SSD) measurement accuracy was within 8 mm in the anterior of the phantom.

CONCLUSIONS

With the CZT signal processing algorithm, the mmWave radar is able to measure the absolute distance to a flat surface within 1 mm. But the absolute distance measurement to a human shape phantom is as large as 8 mm at some angles. Further improvement is necessary to improve the accuracy of SSD measurement to uneven surfaces by the mmWave radar.

Prevalence and impact of viral myocarditis in patients with severe fever with thrombocytopenia syndrome

To explore the association and impact between viral myocarditis and mortality in patients with severe fever with thrombocytopenia syndrome. A dynamic analysis was conducted between fatal group and nonfatal group regarding the daily epidemiology data, clinical symptoms, and electrocardiogram (ECG), echocardiogram, and laboratory findings. Outcomes of patients with and without viral myocarditis were compared. The association between viral myocarditis and mortality was analyzed. Among 183 severe fever with thrombocytopenia syndrome patients, 32 were in the fatal group and 151 in the nonfatal group; there were 26 (81.25%) with viral myocarditis in the fatal group, 66 (43.70%) with viral myocarditis in the nonfatal group (p < 0.001), 79.35% of patients had abnormal ECG results. The abnormal rate of ECG in the fatal group was 100%, and in the nonfatal group was 74.83%. Univariate analysis found that the number of risk factors gradually increased on Day 7 of the disease course and reached the peak on Day 10. Combined with the dynamic analysis of the disease course, alanine aminotransferase, aspartate aminotransferase, creatine kinase, creatine kinase fraction, lactate dehydrogenase, hydroxybutyrate dehydrogenase, neutrophil count, serum creatinine, Na, Ca, carbon dioxide combining power, amylase, lipase, activated partial thromboplastin time and thrombin time had statistically significant impact on prognosis. The incidence of fever with thrombocytopenia syndrome combined with viral myocarditis is high, especially in the fatal group of patients. Viral myocarditis is closely related to prognosis and is an early risk factor. The time point for changes in myocarditis is Day 7 of the course of the disease.

[A survey on the current situation of serum vitamin A and vitamin D levels among children aged 2-<7 years of 20 cities in China]

Objective: To investigate serum vitamin A and vitamin D status in children aged 2-<7 years in 20 cities in China. Methods: A cross-sectional study was conducted. A total of 2 924 healthy children aged 2-<7 years were recruited from September 2018 to September 2019 from 20 cities in China, categorized by age groups of 2-<3 years, 3-<5 years, and 5-<7 years. The demographic and economic characteristics and health-related information of the enrolled children were investigated. Body weight and height were measured by professional staff members. The serum vitamin A and vitamin D levels were detected by high-performance liquid chromatography-tandem mass spectrometry. Chi-square test and Logistic regression were applied to analyze the association between vitamin A and vitamin D deficiency and insufficiency as well as their underlying impact factors. Results: The age of the 2 924 enrolled children was 4.33 (3.42, 5.17) years. There were 1 726 males (59.03%) and 1 198 females (40.97%). The prevalences of vitamin A and vitamin D deficiency in enrolled children were 2.19% (64/2 924) and 3.52% (103/2 924), respectively, and the insufficiency rates were 29.27% (856/2 924) and 22.20% (649/2 924), respectively. Children with both vitamin A and vitamin D deficiencies or insufficiencies were found in 10.50% (307/2 924) of cases. Both vitamin A (χ2=7.91 and 8.06, both P=0.005) and vitamin D (χ2=71.35 and 115.10, both P<0.001) insufficiency rates were higher in children aged 3-<5 and 5-<7 years than those in children aged 2-<3 years. Vitamin A and vitamin D supplementation in the last 3 months was a protective factor for vitamin A and D deficiency and insufficiency, respectively (OR=0.68 and 0.22, 95%CI 0.49-0.95 and 0.13-0.40, both P<0.05). The rates of vitamin A and D insufficiency was higher in children with annual household incomes <60 000 RMB than in those with annual household incomes ≥60 000 RMB (χ2=34.11 and 10.43, both P<0.01). Northwest and Southwest had the highest rates of vitamin A and vitamin D insufficiency in children aged 2-<7 yeas, respectively (χ2=93.22 and 202.54, both P<0.001). Conclusions: Among 20 cities in China, children aged 2-<7 years experience high rates of vitamin A and vitamin D insufficiency, which are affected by age, family economic level, vitamin A and vitamin D supplementation, and regional economic level. The current results suggest that high level of attention should be paid to vitamin A and vitamin D nutritional status of preschool children.

A deep learning approach to remove contrast from contrast-enhanced CT for proton dose calculation

PURPOSE

Non-Contrast Enhanced CT (NCECT) is normally required for proton dose calculation while Contrast Enhanced CT (CECT) is often scanned for tumor and organ delineation. Possible tissue motion between these two CTs raises dosimetry uncertainties, especially for moving tumors in the thorax and abdomen. Here we report a deep-learning approach to generate NCECT directly from CECT. This method could be useful to avoid the NCECT scan, reduce CT simulation time and imaging dose, and decrease the uncertainties caused by tissue motion between otherwise two different CT scans.

METHODS

A deep network was developed to convert CECT to NCECT. The network receives a 3D image from CECT images as input and generates a corresponding contrast-removed NCECT image patch. Abdominal CECT and NCECT image pairs of 20 patients were deformably registered and 8000 image patch pairs extracted from the registered image pairs were utilized to train and test the model. CTs of clinical proton patients and their treatment plans were employed to evaluate the dosimetric impact of using the generated NCECT for proton dose calculation.

RESULTS

Our approach achieved a Cosine Similarity score of 0.988 and an MSE value of 0.002. A quantitative comparison of clinical proton dose plans computed on the CECT and the generated NCECT for five proton patients revealed significant dose differences at the distal of beam paths. V100% of PTV and GTV changed by 3.5% and 5.5%, respectively. The mean HU difference for all five patients between the generated and the scanned NCECTs was ∼4.72, whereas the difference between CECT and the scanned NCECT was ∼64.52, indicating a ∼93% reduction in mean HU difference.

CONCLUSIONS

A deep learning approach was developed to generate NCECTs from CECTs. This approach could be useful for the proton dose calculation to reduce uncertainties caused by tissue motion between CECT and NCECT.

Intravesical chemotherapy synergize with an immune adjuvant by a thermo-sensitive hydrogel system for bladder cancer

Surgical resection remains the prefer option for bladder cancer treatment. However, the effectiveness of surgery is usually limited for the high recurrence rate and poor prognosis. Consequently, intravesical chemotherapy synergize with immunotherapy in situ is an attractive way to improve therapeutic effect. Herein, a combined strategy based on thermo-sensitive PLEL hydrogel drug delivery system was developed. GEM loaded PLEL hydrogel was intravesical instilled to kill tumor cells directly, then PLEL hydrogel incorporated with CpG was injected into both groins subcutaneously to promote immune responses synergize with GEM. The results demonstrated that drug loaded PLEL hydrogel had a sol-gel phase transition behavior in response to physiological temperature and presented sustained drug release, and the PLEL-assisted combination therapy could have better tumor suppression effect and stronger immunostimulating effect in vivo. Hence, this combined treatment with PLEL hydrogel system has great potential and suggests a clinically-relevant and valuable option for bladder cancer.

CT-based online adaptive radiotherapy improves target coverage and organ at risk (OAR) avoidance in stereotactic body radiation therapy (SBRT) for prostate cancer

Introduction

Stereotactic body radiation therapy (SBRT) is an emerging treatment modality for clinically localized prostate cancer (PCa). Online daily adaptive radiotherapy (ART) could potentially improve the therapeutic ratio of prostate SBRT by accounting for inter-fraction variation in target and OAR volumes. To our knowledge, no group has evaluated the clinical utility of a novel AI-augmented CT-based ART system for prostate SBRT. In this study we hypothesized that adaptive prostate SBRT plans would result in improved target coverage and lower dose to OARs in comparison to unadapted treatment plans.

Methods

Seven patients with favorable intermediate to oligometastatic PCa treated with 5-fx prostate adaptive SBRT were retrospectively reviewed. Patients were treated with 3625 cGy to the prostate and seminal vesicles. 6 patients additionally received 2500 cGy to the pelvic nodes, 5 patients underwent a boost to 4000 cGy to the prostate. For each fraction, a CBCT was acquired and OARs (rectum, bladder, bowel, sigmoid, femurs) were segmented/deformed using AI. CTVs were rigidly registered. Volumes were adjusted manually and PTV expansions added. Adaptive treatment plans were developed based on the contoured targets and OARs and dose to these volumes for the adapted vs. initial plans were compared for each fraction. V100 and the D0.03 cc between scheduled and adapted treatment plans were compared using a Student's t-test, with significance threshold of P < 0.05.

Results

Seven patients completed 35 Fx's of adaptive RT. Daily adaptation resulted in a statistically significant mean improvement in PTV V100 for all targets: [21.4 % ± 4.3 % for PTV 4000 (p < 0.0001); 8.7 % ± 1.1 % for PTV 3625 (p < 0.0001); and 11.5 % ± 3.1 % for PTV 2500 (p = 0.0013)]. Mean rectal D0.03 was significantly reduced by 38.8 cGy ± 5.95 cGy (p < 0.0001) per fraction (194 cGy/5 fractions) compared to the initial plans. There was a modest increase in bladder dose of 10.9 cGy ± 4.93 cGy per fraction (p = 0.0424) for the adaptive plans. The adaptive plans met bladder constraints for every fraction. There were no statistically significant differences between sigmoid or bowel dose for adapted vs. initial plans. No patients experienced acute CTCAE grade ≥ 3 GI/GU adverse events (median F/U 9.5 months). All statistically significant differences were maintained in the presence and absence of rectal hydrogel spacer (p < 0.05).

Conclusions

CT-based online adaptive SBRT resulted in statistically significant and clinically meaningful improvements in PTV coverage and D0.03 cc dose to the rectum. A trial evaluating CT adaptive whole-pelvis prostate SBRT is underway.

[Comparison of BCR::ABL (P210) mRNA levels detected by dPCR and qPCR methods in patients with chronic myeloid leukemia]

Objective: To compare digital polymerase chain reaction (dPCR) and real-time quantitative PCR (qPCR) measurements of BCR::ABL (P210) mRNA expression in patients with chronic myeloid leukemia (CML) . Methods: In this non-interventional, cross-sectional study, BCR::ABL (P210) mRNA was simultaneously measured by dPCR and qPCR in peripheral blood samples collected from patients with CML who underwent tyrosine kinase inhibitor therapy and who achieved at least a complete cytogenetic response from September 2021 to February 2023 at Peking University People's Hospital. The difference, correlation, and agreement between the two methods were evaluated using the Wilcoxon signed-rank test, Spearman's correlation, and Bland-Altman analysis, respectively. Results: In total, 459 data pairs for BCR::ABL mRNA expression measured by dPCR and qPCR from 356 patients with CML were analyzed. There was a significant difference in BCR::ABL mRNA expression between the two methods (P<0.001). When analyzed by the depth of the molecular response (MR), a significant difference only existed for patients with ≥MR4.5 (P<0.001). No significant difference was observed for those who did not achieve a major MR (no MMR; P=0.922) or for those who achieved a major MR (MMR; P=0.723) or MR4 (P=0.099). There was a moderate correlation between the BCR::ABL mRNA expression between the two methods (r=0.761, P<0.001). However, the correlation gradually weakened or disappeared as the depth of the MR increased (no MMR: r=0.929, P<0.001; MMR: r=0.815, P<0.001; MR4: r=0.408, P<0.001; MR4.5: r=0.176, P=0.176). In addition, the agreement in BCR::ABL mRNA expression between the two methods in those with MR4.5 was weaker than other groups (no MMR: ▉= 0.042, P=0.846; MMR:▉=0.054, P=0.229; MR4:▉=-0.020, P=0.399; MR4.5:▉=-0.219, P<0.001) . Conclusions: dPCR is more accurate than qPCR for measuring BCR::ABL (P210) mRNA expression in patients with CML who achieve a stable deep MR.

[Evaluation of the application value of seven tumor-associated autoantibodies in non-small cell lung cancer based on machine learning algorithms]

Objective: Based on the diagnostic model established and validated by the machine learning algorithm, to investigate the value of seven tumor-associated autoantibodies (TAABs), namely anti-p53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGEA1 and CAGE antibodies in the diagnosis of non-small cell lung cancer (NSCLC) and to differentiate between NSCLC and benign lung nodules. Methods: This was a retrospective study of clinical cases. Model building queue: a total of 227 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from November 2018 to June 2021 were collected as the NSCLC group, and 120 cases of benign lung nodules, 122 cases of pneumonia and 120 healthy individuals were selected as the control groups. External validation queue: a total of 100 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from May 2022 to December 2022 were collected as the NSCLC group, and 36 cases of benign lung nodules, 32 cases of pneumonia and 44 healthy individuals were selected as the control groups. In addition, NSCLC was divided into early (stage 0-ⅠB) and mid-to-late (stage ⅡA-ⅢB) subgroups. The levels of 7-TAABs were detected by enzyme immunoassay, and serum concentrations of CEA and CYFRA21-1 were detected by electrochemiluminescence. Four machine learning algorithms, XGBoost, Lasso logistic regression, Naïve Bayes, and Support Vector Machine are used to establish classification models. And the best performance model was chosen based on evaluation metrics and a multi-indicator combination model was established. In addition, an online risk evaluation tool was generated to assist clinical applications. Results: Except for p53, the levels of rest six TAABs, CEA and CYFRA21-1 were significantly higher in the NSCLC group (P<0.05). Serum levels of anti-SOX2 [1.50 (0.60, 10.85) U/ml vs. 0.8 (0.20, 2.10) U/ml, Z=2.630, P<0.05] and MAGEA1 antibodies [0.20 (0.10, 0.43) U/ml vs. 0.10 (0.10, 0.20) U/ml, Z=2.289, P<0.05], CEA [3.13 (2.12, 5.64) ng/ml vs. 2.11 (1.25, 3.09) ng/ml, Z=3.970, P<0.05] and CYFRA21-1 [4.31(2.37, 7.14) ng/ml vs. 2.53(1.92, 3.48) ng/ml, Z=3.959, P<0.05] were significantly higher in patients with mid-to late-stage NSCLC than in early stages. XGBoost model was used to establish a multi-indicator combined detection model (after removing p53). 6-TAABs combined with CYFRA21-1 was the best combination model for the diagnosis of NSCLC and early NSCLC. The optimal diagnostic thresholds were 0.410, 0.701 and 0.744, and the AUC was 0.828, 0.757 and 0.741, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in model building queue, and the AUC was 0.760, 0.710 and 0.660, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in external validation queue. Conclusion: In the diagnosis of NSCLC, 6-TAABs is superior to that of traditional tumor markers CEA and CYFRA21-1, and can compensate for the shortcomings of traditional tumor markers. For the differential diagnosis of NSCLC and benign lung nodule, "6-TAABs+CYFRA21-1" is the most cost-effective combination, and plays an important role in prevention and screening for early lung cancer.

EStore: A User-Friendly Encrypted Storage Scheme for Distributed File Systems

In this paper, we propose a user-friendly encrypted storage scheme named EStore, which is based on the Hadoop distributed file system. Users can make use of cloud-based distributed file systems to collaborate with each other. However, most data are processed and stored in plaintext, which is out of the owner's control after it has been uploaded and shared. Meanwhile, simple encryption guarantees the confidentiality of uploaded data but reduces availability. Furthermore, it is difficult to deal with complex key management as there is the problem whereby a single key encrypts different files, thus increasing the risk of leakage. In order to solve the issues above, we put forward an encrypted storage model and a threat model, designed with corresponding system architecture to cope with these requirements. Further, we designed and implemented six sets of protocols to meet users' requirements for security and use. EStore manages users and their keys through registration and authentication, and we developed a searchable encryption module and encryption/decryption module to support ciphertext retrieval and secure data outsourcing, which will only minimally increase the calculation overhead of the client and storage redundancy. Users are invulnerable compared to the original file system. Finally, we conducted a security analysis of the protocols to demonstrate that EStore is feasible and secure.

Performance of Adaptive Deep Learning Models for Dose Predictions on High-Quality Cone-Beam Computed Tomography Images

PURPOSE/OBJECTIVE(S)

Online plan generation remains a patient-specific and time-consuming process that can place a significant burden on clinics strained with staffing shortages. As previous research show that dose-volume histogram (DVH) prediction plays a crucial role in automatic treatment planning, the objective of this study is to assess the capability of adaptive deep learning models in predicting dose information in volumetric modulation radiotherapy plans using the high-quality CBCT images and contour information of organs-at-risk (OARs).

MATERIALS/METHODS

The relationship between dose-volume histograms (DVHs) in radiotherapy plans and the geometric information of organs-at-risk (OAR) and planning target volume (PTV) has been well established. To evaluate the performance of the current state-of-the-art convolutional neural network (CNN) models including VIT3D and Unet3D, and intuitive machine learning methods (i.e., SVM and MLP), we implemented those models for dose prediction and conducted a comprehensive analysis with treatment plans created from images acquired from patients who consented to participate an IRB-approved imaging study designed to evaluate the imaging performance of the system. In total, 20 plans created by certified medical dosimetrists were employed in this study, with 15 used for training the machine-learning models and the remaining 5 used for performance testing. Two evaluation metrics were used: 1) root mean square error (RMSE) of the predicted dose and true dose and 2) time spent on dose prediction.

RESULTS

The results of the analysis showed that the ViT-3D (Transformer) model had the lowest RMSE of 3.682 ±0.010, followed by the Unet-3D (CNN) model with an RMSE of. 3.973 ±0.021 The MLP model had an RMSE of 8.007 ±0.019 while the SVM model had the highest RMSE of 9.156 ±0.032. For a fair comparison, we use 4-fold cross validation (each has 15 training plans and 5 testing plans), and report the mean value with standard deviation. All models are optimized with Adam optimizer of a learning rate 0.01, and the training process is stopped after 100 epochs. These findings indicate that the ViT-3D (Transformer) model performed the best in terms of predicting the dose information in volumetric modulation radiotherapy plans based on the CBCT images and contour information of OARs. For tested plan which contains 81 CT images (512 × 512 resolution), the inference time to predict dose information with a general CPU machine (6-Core Intel Core i7) is about 1.5 minutes. With GPU resources, such as NVIDIA A100, the inference process can be finished within seconds.

CONCLUSION

The study demonstrated that current state-of-the-art machine-learning models can achieve promising accuracy in dose prediction using high-quality CBCT images. A well-trained machine-learning model could offer clinicians a quick and reliable prediction of the true dose to patients in the case of significant anatomical changes or provide patient-specific optimization objectives if replanning is warranted.

Accuracy of Electron Density and Planning Dosimetry in a Novel High-Quality CBCT Imaging System

PURPOSE/OBJECTIVE(S)

A high-quality Cone-Beam Computed Tomography (CBCT) imaging system has been FDA approved for imaging guidance and dose calculation in radiotherapy. This study aims to evaluate the accuracy of the relative electron density in CBCT images acquired in this CBCT imaging system in a phantom study and its dosimetric impact on treatment planning in a patient study.

MATERIALS/METHODS

Astoichiometric CT calibration was performed with a CIRS phantom (SunNuclear, Model 062M) to generate the HU-electron density curve for two tube voltages, 125kVp and 140 kVp, respectively. The phantom has a longitudinal length of 26.5 cm and is equipped with interchangeable inserts of various compositions, supplied by the vendor. Measurements were taken with solid water plates added to both ends of the phantom to allow adequate scattering and repeated for various clinical protocols with different combinations of tube voltages and exposures. The accuracy of the relative electron density of the CBCT imaging system was verified by comparing the calculated electron density from the Hounsfield Units (HU) measurements obtained from a Gammex phantom to the relative electron densities provided in vendor's specifications. To benchmark the relative electron density of the CBCT imaging system against a standard helical CT simulator, ten clinical plans that were created on CT simulation images were copied and recalculated on the CBCT images acquired immediately after the CT simulation, the latter of which was a standard procedure in current radiotherapy care for all patients who had given their consent to participate in the IRB-approved imaging study. The dose grids used in these calculations were 2.5mm x 2.5mm x 3mm. The Gamma passing rate was calculated using a standard 3mm/3% criterion with a 10% threshold.

RESULTS

Ourresults showed the difference between the averaged CBCT calibration curves acquired at tube voltages of 125 kVP and 140 kVp was less than 2%. The mean discrepancy of the relative electron densities from vendor's specification was 0.0045 with a range between -0.02 and 0.04. Relative electron densities in all inserts were within 2% from the vendor's specifications except the cortical bone insert. Gamma passing rate was between 96.02% and 98.49% with mean value of 97.4% and a standard deviation of 0.95%. We consider this reflects the fact that the CT simulation and CBCT imaging were performed in separated rooms, which resulted in slight anatomical deformation that could negatively impact the Gamma passing rate.

CONCLUSION

The CBCT imaging system provides sufficient accuracy of electron density for dose calculation, and the dose distribution calculated on the CBCT images is clinically equivalent to those calculated on helical CT images. The enhanced imaging quality of CBCT could further extend the role of imaging guidance to planning for adaptive radiotherapy, potentially reducing the need for re-simulation and interruptions in the radiotherapy course.

An In Silico study of a One-Day One-Machine Workflow for Definitive Radiotherapy Cases on a Novel Simulation and Treatment Platform

PURPOSE/OBJECTIVE(S)

The workflow in Radiotherapy (RT) has largely unchanged for the past three decades, despite increasing evidence suggesting that delayed access to RT, including the wait time between consultation, simulation, and treatment appointments, can negatively impact clinical outcomes. In this pilot study, we present preliminary results of an in silico study that demonstrate the feasibility of a novel RT platform, which integrates simulation into the treatment process and enables patients to receive immediate RT after their initial RT consultation.

MATERIALS/METHODS

A prospective clinical study has been approved to assess the capabilities of a novel RT platform with a high quality CBCT system for imaging guidance as well as planning. This new platform enables a novel clinical workflow that allows clinicians to review contours and plans created on diagnostic CT images prior to the initial RT consultation and allow them to approve new plans adapted on the actual simulation dataset acquired on the first treatment fraction. Four patients receiving standard of care RT (three abdomen and one thorax) consented for this study and underwent additional experimental CBCT simulation on the new platform in addition to their standard CT simulation. The CBCT simulation was taken in two setups: with a specific mold on a flat couch and without a mold on a curved couch. To demonstrate the equivalence of the new workflow to the current standard of care, the plan created on the most recent diagnostic CT images was compared to the plans adapted on the experimental simulation images and the standard CT simulation images, using a knowledge-based model. Contours were propagated from approved datasets to the new datasets through deformable image registration.

RESULTS

All experimental simulations were completed between 14 and 21 minutes with the assistance of two therapists. The contouring, editing, and replanning process took less than one hour in all cases, in line with our experience and peer-reviewed literature. Despite notable anatomical changes observed, the dose-volume histograms (DVH) were consistent, as shown in Table 1.

CONCLUSION

The novel workflow presented herein was feasible and demonstrates that the integration of simulation with image-guided RT on one single platform may unlock the potential of accelerating the RT workflow and reducing the wait time for treatment from weeks to hours.

Proton Online Adaptation Using Novel Cone-Beam Computed Tomography System

PURPOSE/OBJECTIVE(S)

Cone beam computed tomography (CBCT) has been used in clinic frequently to provide quick, online, and handy three-dimensional images. However, due to its significant artifacts and inaccurate Hounsfield values (HU), CBCT based online proton adaptation is infeasible. Recently, a novel in-room imaging solution was developed to allow larger images, better contrast and faster CBCT imaging acquisition. Our work demonstrated for the first time the feasibility of using this novel CBCT images for direct intensity modulated proton planning.

MATERIALS/METHODS

Three patients and three CIRS phantoms were scanned using novel imaging technique (CBCTp) for this work. CT curves were acquired by scanning a CIRS electron density phantom. Stopping power ratio was computed using the stoichiometric method. Proton plans were made on treatment simulation CT and further evaluated on CBCTp to compare the differences.

RESULTS

The table below shows three patients and three phantoms plan comparisons. Multiple sites and dose levels were studied. The planning target volume (PTV) coverage (D95%) and mean dose difference between simulation CT and CBCTp are 0.8% and 0.3%, correspondingly. Dosimetrically, phantom and patient plans are almost identical between two imaging techniques. Lung patient plan show the largest variation due to patient tumor change and the quality of breathing.

CONCLUSION

The novel and high quality of CBCT is feasible for direct proton planning with accurate CT calibration. It provides a reliable alternative solution for proton online adaptive therapy.

Initial clinical experience building a dual CT- and MR-guided adaptive radiotherapy program

Introduction

Our institution was the first in the world to clinically implement MR-guided adaptive radiotherapy (MRgART) in 2014. In 2021, we installed a CT-guided adaptive radiotherapy (CTgART) unit, becoming one of the first clinics in the world to build a dual-modality ART clinic. Herein we review factors that lead to the development of a high-volume dual-modality ART program and treatment census over an initial, one-year period.

Materials and Methods

The clinical adaptive service at our institution is enabled with both MRgART (MRIdian, ViewRay, Inc, Mountain View, CA) and CTgART (ETHOS, Varian Medical Systems, Palo Alto, CA) platforms. We analyzed patient and treatment information including disease sites treated, radiation dose and fractionation, and treatment times for patients on these two platforms. Additionally, we reviewed our institutional workflow for creating, verifying, and implementing a new adaptive workflow on either platform.

Results

From October 2021 to September 2022, 256 patients were treated with adaptive intent at our institution, 186 with MRgART and 70 with CTgART. The majority (106/186) of patients treated with MRgART had pancreatic cancer, and the most common sites treated with CTgART were pelvis (23/70) and abdomen (20/70). 93.0% of treatments on the MRgART platform were stereotactic body radiotherapy (SBRT), whereas only 72.9% of treatments on the CTgART platform were SBRT. Abdominal gated cases were allotted a longer time on the CTgART platform compared to the MRgART platform, whereas pelvic cases were allotted a shorter time on the CTgART platform when compared to the MRgART platform. Our adaptive implementation technique has led to six open clinical trials using MRgART and seven using CTgART.

Conclusions

We demonstrate the successful development of a dual platform ART program in our clinic. Ongoing efforts are needed to continue the development and integration of ART across platforms and disease sites to maximize access and evidence for this technique worldwide.

[Association between different obesity measurement indexes and serum C-reactive protein in adult women]

Objective: To explore the association of different obesity measurement indexes on serum C-reactive protein (CRP) in Chinese adult women. Methods: The data were obtained from baseline and follow-up surveys of the urban Breast Cancer Screening Program in Shuangliu District, Chengdu. A total of 441 adult women were included in the study. A questionnaire survey, physical examination, and laboratory testing were conducted on the subjects. Multivariate logistic regression model, two-level mixed effects logistic regression model, and restricted cubic spline method were used to investigate the linear and nonlinear correlation between different obesity measurement indexes and serum CRP in adult women. Results: For every 1 unit increase in BMI, waist circumference (WC), and adiposity, the risk of elevated serum CRP or exacerbation of chronic low-grade inflammation in adult women increased by 16.5%, 5.0%, and 11.1% (P<0.05), respectively. Both BMI and adiposity were nonlinear correlated with serum CRP. Using BMI=24.0 kg/m2 as the reference point, serum CRP level increased with the increase of BMI when BMI >24.0 kg/m2. Using adiposity=30% as the reference point, serum CRP level increased with the increase of adiposity when adiposity >30%. Conclusions: Overall, obesity reflected by BMI had the strongest association with serum CRP in adult women, followed by body fat content reflected by adiposity, and central obesity reflected by WC had the weakest association with CRP. Adult women with BMI >24.0 kg/m2 or adiposity >30% are at high risk for obesity-related inflammatory manifestations.

[Identification and 3D architecture analysis of the LIPC gene mutation in a pedigree with familial hypercholesterolemia-like phenotype]

Objective: To identify and analyze 3D architecture of the mutational sites of susceptible genes in a pedigree with familial hypercholesterolemia-like phenotype (FHLP). Methods: This is a case series study. A pedigree with suspected familial hypercholesterolemia was surveyed. The proband admitted in Beijing Anzhen Hospital in April 2019. Whole-exome sequencing was performed to determine the mutational sites of susceptible genes in the proband. Polymerase chain reaction (PCR) sequencing was used to verify the pathogenic variant on proband's relatives. The structural and functional changes of the proteins were analyzed and predicted by Discovery Studio 4.0 and PyMol 2.0. Results: The patients in the pedigree showed abnormal lipid profiles, especially elevated levels of total cholesterol(TC). The genetic screening detected the c.1330C>T SNP in the exon 8 of lipase C (LIPC) gene, this mutation leads to an amino acid substitution from arginine to cysteine at position 444 (Arg444Cys), in the proband and proband's father and brother. In this family, members with this mutation exhibited elevated TC, whereas lipid profile was normal from the proband's mother without this mutation. This finding indicated that LIPC: c.1330C>T mutation might be the mutational sites of susceptible genes. The analysis showed that Arg444Cys predominantly affected the ligand-binding property of the protein, but had a limited impact on catalytic function. Conclusion: LIPC: c.1330C>T is a new mutational site of susceptible genes in this FHLP pedigree.

[Comparison of diagnostic performance of Clear Cell Likelihood Score v1.0 and v2.0 for clear renal cell carcinoma]

OBJECTIVE

To compare the performance of Clear Cell Likelihood Score (ccLS) v1.0 and v2.0 in diagnosing clear cell renal cell carcinoma (ccRCC) from small renal masses (SRM).

METHODS

We retrospectively analyzed the clinical data and MR images of patients with pathologically confirmed solid SRM from the First Medical Center of the Chinese PLA General Hospital between January 1, 2018, and December 31, 2021, and from Beijing Friendship Hospital of Capital Medical University and Peking University First Hospital between January 1, 2019 and May 17, 2021. Six abdominal radiologists were trained for use of the ccLS algorithm and scored independently using ccLS v1.0 and ccLS v2.0. Random- effects logistic regression modeling was used to generate plot receiver operating characteristic curves (ROC) to evaluate the diagnostic performance of ccLS v1.0 and ccLS v2.0 for ccRCC, and the area under curve (AUC) of these two scoring systems were compared using the DeLong's test. Weighted Kappa test was used to evaluate the interobserver agreement of the ccLS score, and differences in the weighted Kappa coefficients was compared using the Gwet consistency coefficient.

RESULTS

In total, 691 patients (491 males, 200 females; mean age, 54 ± 12 years) with 700 renal masses were included in this study. The pooled accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ccLS v1.0 for diagnosing ccRCC were 77.1%, 76.8%, 77.7%, 90.2%, and 55.7%, as compared with 80.9%, 79.3%, 85.1%, 93.4%, 60.6% with ccLS v2.0, respectively. The AUC of ccLS v2.0 was significantly higher than that of ccLS v1.0 for diagnosis of ccRCC (0.897 vs 0.859; P < 0.01). The interobserver agreement did not differ significantly between ccLS v1.0 and ccLS v2.0 (0.56 vs 0.60; P > 0.05).

CONCLUSION

ccLS v2.0 has better performance for diagnosing ccRCC than ccLS v1.0 and can be considered for use to assist radiologists with their routine diagnostic tasks.

Toward discovering a novel family of peptides targeting neuroinflammatory states of brain microglia and astrocytes

Microglia are immune-derived cells critical to the development and healthy function of the brain and spinal cord, yet are implicated in the active pathology of many neuropsychiatric disorders. A range of functional phenotypes associated with the healthy brain or disease states has been suggested from in vivo work and were modeled in vitro as surveying, reactive, and primed sub-types of primary rat microglia and mixed microglia/astrocytes. It was hypothesized that the biomolecular profile of these cells undergoes a phenotypical change as well, and these functional phenotypes were explored for potential novel peptide binders using a custom 7 amino acid-presenting M13 phage library (SX7) to identify unique peptides that bind differentially to these respective cell types. Surveying glia were untreated, reactive were induced with a lipopolysaccharide treatment, recovery was modeled with a potent anti-inflammatory treatment dexamethasone, and priming was determined by subsequently challenging the cells with interferon gamma. Microglial function was profiled by determining the secretion of cytokines and nitric oxide, and expression of inducible nitric oxide synthase. After incubation with the SX7 phage library, populations of SX7-positive microglia and/or astrocytes were collected using fluorescence-activated cell sorting, SX7 phage was amplified in Escherichia coli culture, and phage DNA was sequenced via next-generation sequencing. Binding validation was done with synthesized peptides via in-cell westerns. Fifty-eight unique peptides were discovered, and their potential functions were assessed using a basic local alignment search tool. Peptides potentially originated from proteins ranging in function from a variety of supportive glial roles, including synapse support and pruning, to inflammatory incitement including cytokine and interleukin activation, and potential regulation in neurodegenerative and neuropsychiatric disorders.

Characterization of the Targeting Accuracy of a Neuronavigation-Guided Transcranial FUS System In Vitro, In Vivo, and In Silico

Focused ultrasound (FUS)-enabled liquid biopsy (sonobiopsy) is an emerging technique for the noninvasive and spatiotemporally controlled diagnosis of brain cancer by inducing blood-brain barrier (BBB) disruption to release brain tumor-specific biomarkers into the blood circulation. The feasibility, safety, and efficacy of sonobiopsy were demonstrated in both small and large animal models using magnetic resonance-guided FUS devices. However, the high cost and complex operation of magnetic resonance-guided FUS devices limit the future broad application of sonobiopsy in the clinic. In this study, a neuronavigation-guided sonobiopsy device is developed and its targeting accuracy is characterized in vitro, in vivo, and in silico. The sonobiopsy device integrated a commercially available neuronavigation system (BrainSight) with a nimble, lightweight FUS transducer. Its targeting accuracy was characterized in vitro in a water tank using a hydrophone. The performance of the device in BBB disruption was verified in vivo using a pig model, and the targeting accuracy was quantified by measuring the offset between the target and the actual locations of BBB opening. The feasibility of the FUS device in targeting glioblastoma (GBM) tumors was evaluated in silico using numerical simulation by the k-Wave toolbox in glioblastoma patients. It was found that the targeting accuracy of the neuronavigation-guided sonobiopsy device was 1.7 ± 0.8 mm as measured in the water tank. The neuronavigation-guided FUS device successfully induced BBB disruption in pigs with a targeting accuracy of 3.3 ± 1.4 mm. The targeting accuracy of the FUS transducer at the GBM tumor was 5.5 ± 4.9 mm. Age, sex, and incident locations were found to be not correlated with the targeting accuracy in GBM patients. This study demonstrated that the developed neuronavigation-guided FUS device could target the brain with a high spatial targeting accuracy, paving the foundation for its application in the clinic.

[Preliminary study on the effect of fecal microbiota transplantation on neurobehavior and gut microbiota of offspring rats exposed to arsenic]

Objective: To explore the effects of fecal microbiota transplantation (FMT) on neurobehavior and gut microbiota of arsenic-exposed offspring rats. Methods: In April 2021, Thirty-six SPF SD rats aged 8 weeks were seleted, rats were ranked by weight and divided into four groups according to randomized block design, namely control group, arsenic exposure group (As group) , arsenic+normal saline group (As+NaCl group) and As+FMT group, 6 females and 3 males in each group. Fecal microbiota fluid were provided by feces of rats in control group. Rats drank tap water containing 75 mg/L sodium arsenite for one week and then were caged together. The arsenic exposure was terminated until the pups were born. Female rats with vaginal plug were treated with fecal microbiota fluid via gavage during neurodevelopmental teratogenic window period. The volume of gavage was 1 ml/100 g with once every two days, for a total of three times. Weight alterations of offspring rats were recorded every week after weaning, and when offspring rats grew up for 6 weeks, Morris test and open field experiment was used to observe learning and memory abilities, as well as neurobehavioral performance of autonomous exploration and tension, respectively. 16S rDNA sequencing technology was used to detect microbiota diversities in fecal samples of rats in As group and As+FMT group. Results: Compared with the control group, the ratio of swimming distance and staying time in the target quadrant and the times of crossing the platform of rats in As group decreased significantly, and the motor distance, times entering central zone and the number of grid crossing of rats decreased significantly (P<0.05) . Compared with As group, the ratio of swimming distance in target quadrant, the motor distance in central zone and times entering central zone of rats in As+FMT group were evidently increased (P<0.05) . The analysis of fecal microbiota diversities showed that, at the phyla level, the relative abundance of Bacteroidetes in feces of rats in As+FMT group was higher than that in As group (68.34% vs 60.55%) , while the relative abundance of Firmicutes was lower than that in As group (28.02% vs 33.48%) . At the genus level, the relative abundance of Prevotella in As+FMT group was significantly higher than that in As group, becoming the dominant genus (42.08% vs 21.78%) . Additionally, compared with As group, a total of 22 genus were increased with 21 decreased genus in As+FMT group (P<0.05) . LEfSe analysis showed that dominant genuses in As+FMT group were Prevotella and UCG_005, and their relative abundance was significantly higher than that of As group (P<0.05) . Conclusion: FMT may alleviate the impaired learning and memory ability and anxiety like behavior of the offspring rats exposed to arsenic, and improve the disrupted gut microbiota.

Dynapenic Abdominal Obesity and Risk of Heart Disease among Middle-Aged and Older Adults: A Prospective Cohort Study

OBJECTIVES

The vicious cycle of dynapenia and abdominal obesity may have synergistic detrimental impacts on health. We aim to investigate the prospective association between dynapenic abdominal obesity and the risk of heart disease among middle-aged and older adults.

DESIGN

A prospective cohort study.

SETTING

English Longitudinal Study of Ageing, 2002-2019.

PARTICIPANTS

A total of 4734 participants aged 50 years and older were included.

MEASUREMENTS

Individuals were divided into non-dynapenia/non-abdominal obesity (ND/NAO), non-dynapenia/abdominal obesity (ND/AO), dynapenia/non-abdominal obesity (D/NAO), and dynapenia/abdominal obesity (D/AO) according to grip strength and waist circumference at baseline. The Cox proportional hazards models were used to obtain the hazard ratios (HRs) of incident heart disease associated with dynapenia and abdominal obesity after adjusting for potential confounding factors.

RESULTS

During a median follow-up of 9.5 years, 1040 cases of heart disease were recorded. Compared with ND/NAO group, the multivariable HRs were 1.05 (0.92, 1.21) for ND/AO group, 1.31 (0.96, 1.81) for D/NAO group, and 1.39 (1.03, 1.88) for D/AO group. The significant association of D/AO with incident heart disease was detected in women but not in men [HR = 1.55 (1.07, 2.24) and 1.06 (0.60, 1.88), respectively]. Among middle-aged adults, significant associations of D/NAO and D/AO with incident heart disease were observed [HR = 2.46 (1.42, 4.29) and 1.74 (1.02, 2.97), respectively].

CONCLUSION

Both D/NAO and D/AO might increase the risk of developing heart disease, highlighting the importance of dynapenia and obesity early screening for heart disease prevention.

A clinical and time savings evaluation of a deep learning automatic contouring algorithm

Automatic contouring algorithms may streamline clinical workflows by reducing normal organ-at-risk (OAR) contouring time. Here we report the first comprehensive quantitative and qualitative evaluation, along with time savings assessment for a prototype deep learning segmentation algorithm from Siemens Healthineers. The accuracy of contours generated by the prototype were evaluated quantitatively using the Sorensen-Dice coefficient (Dice), Jaccard index (JC), and Hausdorff distance (Haus). Normal pelvic and head and neck OAR contours were evaluated retrospectively comparing the automatic and manual clinical contours in 100 patient cases. Contouring performance outliers were investigated. To quantify the time savings, a certified medical dosimetrist manually contoured de novo and, separately, edited the generated OARs for 10 head and neck and 10 pelvic patients. The automatic, edited, and manually generated contours were visually evaluated and scored by a practicing radiation oncologist on a scale of 1-4, where a higher score indicated better performance. The quantitative comparison revealed high (> 0.8) Dice and JC performance for relatively large organs such as the lungs, brain, femurs, and kidneys. Smaller elongated structures that had relatively low Dice and JC values tended to have low Hausdorff distances. Poor performing outlier cases revealed common anatomical inconsistencies including overestimation of the bladder and incorrect superior-inferior truncation of the spinal cord and femur contours. In all cases, editing contours was faster than manual contouring with an average time saving of 43.4% or 11.8 minutes per patient. The physician scored 240 structures with > 95% of structures receiving a score of 3 or 4. Of the structures reviewed, only 11 structures needed major revision or to be redone entirely. Our results indicate the evaluated auto-contouring solution has the potential to reduce clinical contouring time. The algorithm's performance is promising, but human review and some editing is required prior to clinical use.

Extracellular vesicles derived from mesenchymal stem cells confer protection against intervertebral disc degeneration through a microRNA-217-dependent mechanism

OBJECTIVE

Extracellular vesicles released by mesenchymal stem cells (MSC-EVs) can be applied to alleviate intervertebral disc degeneration (IVDD) by curbing apoptosis of nucleus pulposus cells (NPCs). The current study aims to evaluate the effect of MSC-EVs on NPC apoptosis and IVDD and the related regulatory mechanisms involving microRNA (miR)-217.

METHOD

Expression of miR-217 was examined in tumor necrosis factor-α (TNF-α)-induced NPCs and MSC-EVs, followed by identification in the relationship between miR-217, enhancer of zeste homolog 2 (EZH2) and forkhead box O-3 (FOXO3). After isolation of EVs from MSCs and subsequent co-culture with NPCs, we assessed effects of miR-217 on NPC viability, autophagy, senescence and apoptosis along with extracellular matrix (ECM) degradation. Further in vivo experiments were conducted in rat models of IVDD to substantiate the effect of miR-217 on IVDD.

RESULTS

Poor miR-217 expression was found in TNF-α-induced NPCs, while high miR-217 expression was identified in MSC-EVs (P < 0.05). MSC-EVs transferred miR-217 to NPCs and increased its expression, thus attenuating NPC apoptosis and ECM degradation (elevated collagen II and aggrecan but reduced MMP13 and ADAMTS5) (P < 0.05). miR-217 targeted EZH2, and EZH2 bound to the FOXO3 promoter and consequently downregulated its expression. FOXO3 restrained NPC apoptosis and ECM degradation by stimulating cell autophagy (P < 0.05). Furthermore, in vivo experimental results confirmed the suppressive role of miR-217 shuttled by MSC-EVs in IVDD.

CONCLUSION

Overall, the delivery of miR-217 may be a novel mechanism underlying the effect of MSC-EVs on NPC apoptosis and ECM degradation following IVDD.

Binary acoustic metasurfaces for dynamic focusing of transcranial ultrasound

Transcranial focused ultrasound (tFUS) is a promising technique for non-invasive and spatially targeted neuromodulation and treatment of brain diseases. Acoustic lenses were designed to correct the skull-induced beam aberration, but these designs could only generate static focused ultrasound beams inside the brain. Here, we designed and 3D printed binary acoustic metasurfaces (BAMs) for skull aberration correction and dynamic ultrasound beam focusing. BAMs were designed by binarizing the phase distribution at the surface of the metasurfaces. The phase distribution was calculated based on time reversal to correct the skull-induced phase aberration. The binarization enabled the ultrasound beam to be dynamically steered along wave propagation direction by adjusting the operation frequency of the incident ultrasound wave. The designed BAMs were manufactured by 3D printing with two coding bits, a polylactic acid unit for bit “1” and a water unit for bit “0.” BAMs for single- and multi-point focusing through the human skull were designed, 3D printed, and validated numerically and experimentally. The proposed BAMs with subwavelength scale in thickness are simple to design, easy to fabric, and capable of correcting skull aberration and achieving dynamic beam steering.

POS0720 LOW-DOSE GLUCOCORTICOIDS WITHDRAWN IN SYSTEMIC LUPUS ERYTHEMATOSUS: A DESIRABLE AND ATTAINABLE GOAL

Background

Prolonged use of GC may cause irreversible organ damage, leading to impaired quality of life and even increased mortality. However, many physicians are worried about severe flares after GC withdrawal in daily practice.

Objectives

To assess the risk of flare in systemic lupus erythematosus (SLE) patients after low dose glucocorticoids (GC) discontinuation and evaluate the risk factors of flare.

Methods

SLE patients who ever discontinued GC were identified from PKUFHS cohort. The disease flare profile after GC discontinuation were analyzed. Flare rate was analyzed using Kaplan-Meier analysis. COX regression was used to determine the effect of variables on SLE flare. A prognostic nomogram using Cox proportional hazards regression modeling were developed.

Results

132 SLE patients were eligible for the final analysis. They were followed up for a median (IQR) period of 21.8 (9.01, 36.7) months. The cumulative probability of flare after GC discontinuation was 8.3 % at 6 months, 16.8% at year 1 and 27.5% at year 2 (Figure 1A). In multivariate COX analysis, hypocomplementemia and serologically active clinically quiescent (SACQ) were independent risk factors of flare [HR 2.53, 95% CI (1.32, 4.88); HR 3.17, 95% CI (1.44, 6.97), respectively]. Age ≥ 40y at GC withdrawal and hydroxychloroquine usage were independent protective factors of flare [HR 0.53, 95% CI (0.29, 0.99); HR 0.32, 95% CI (0.17, 0.62), respectively] (Table 1). The protective effect of hydroxychloroquine was dosage related. From the prospective of different tapering strategies embodied as duration from prednisone 5mg/d to complete discontinuation, slower tapering strategy (12-24 months) significantly reduced the risk of flare compared to faster tapering strategy (< 3 months) [HR 0.30, 95% CI (0.11, 0.82), p=0.019]. The prognostic nomogram including aforementioned factors effectively predicted 1- and 2-year probability of flare-free (Figure 1B).

Table 1.

Predictors of flare by univariate and multivariate COX analysis.

UnivariatepMultivariatepMultivariatepModel 1Model 2age≥40y at GC withdrawal0.59 (0.33,1.07)0.0840.53 (0.29, 0.99)0.0490.63 (0.33, 1.18)0.147Age at onset ≥18y2.03 (0.62, 6.66)0.2442.75 (0.77, 9.85)0.1212.88 (0.81, 10.2)0.103Remission duration≥60 months since the last flare0.66 (0.35, 1.27)0.2170.81 (0.41, 1.57)0.5260.73 (0.38, 1.41)0.346history of thrombocytopenia1.73 (0.94, 3.18)0.0771.36 (0.70, 2.65)0.3591.45 (0.74, 2.83)0.278history of lupus nephritis0.86 (0.47, 1.55)0.610////Hypocomplementemia1.97 (1.06, 3.66)0.0312.53 (1.32, 4.88)0.005//anti-dsDNA positive1.25 (0.70, 2.23)0.456////SACQ (both)2.91 (1.38, 6.15)0.005//3.17 (1.44, 6.97)0.004SACQ (or)1.29 (0.73, 2.30)0.380////Hydroxychloroquine or not0.29 (0.16, 0.53)<0.0010.29 (0.15, 0.56)<0.0010.32 (0.17, 0.62)0.001Immunosuppressant or not0.77 (0.40, 1.48)0.426////

There was strong collinearity between hypocomplementemia and SACQ, so the two parameters were separated into two models. SACQ (both): anti-dsDNA positive and hypocomplementemia; SACQ (or): anti-dsDNA positive or hypocomplementemia; GC: glucocorticoids. Data were shown as HR (95% CI).

Figure 1.

Conclusion

Low-dose GC is feasibly discontinued with infrequent flare in real-life setting. SACQ and younger age are potential risk factors of SLE flare, while hydroxychloroquine usage and slow GC tapering to withdrawal can reduce relapse. The visualized model we developed may help to predict risk of flare among SLE patients who discontinued GC.

Disclosure of Interests

None declared

The Prembion® pre-biotic improves the impact of anti-CTLA4 immune checkpoint inhibitor in a murine model of malignant pleural mesothelioma

Objective

Immune checkpoint inhibition (ICI) therapy has revolutionized the outcome of certain cancers such as malignant pleural mesothelioma (MPM). However, patient responsiveness to this treatment remains unpredictable. Recently, a role for the gut microbiota composition has emerged for patients to generate a robust immune response against their tumors, following immunotherapy. Here, we studied the impact of Prembion®, a pre-biotic and modulator of the gut microbiota, on tumor control and lymphocyte infiltration in a murine MPM model treated by ICI.

Methods

Prembion® (diluted into drinking water) was administrated to BALBc mice for 14 days. These animals were then inoculated orthotopically with a syngeneic MPM cell line (AB12-luc cells injected in the pleura) and followed by bioluminescence imaging. We determined the tumor growth and mouse survival in different groups: untreated control, Prembion®, IgG control, anti-PDL-1, anti-CTLA4, Prembion®+anti-PDL-1 and Prembion®+anti-CTLA4. A correlation between tumor response/animal survival and MPM infiltration with CD8+ lymphocytes was also performed by immunohistochemistry.

Results

Prembion® was well tolerated and did not affect animal weight or activity. Interestingly, Prembion® was as effective as anti-PDL1 and anti-CTLA4 monotherapy on tumor control, prolonging survival by 4.0 ± 1.1 days compared to controls (p&lt;0.05). Moreover Prembion® potentiated anti-CTLA4 efficacy with a significant improvement in mouse survival of the Prembion®+anti-CTLA4 compared to controls (3.6 ± 1.1 days, p&lt;0.05). Additionally, this finding correlated with enhanced MPM infiltration by CD8+ lymphocytes compared to controls (p&lt;0.05).

Conclusion

Prembion® positively regulated the adaptive immune response against MPM and helped to improve the impact of anti-CTLA4 ICI on MPM. Further work focusing on the gut microbiome changes induced by Prembion® are ongoing to better understand the mechanisms involved.

OP0142 COMPARISON OF ATTAINMENT AND PROTECTIVE EFFECTS OF THE LUPUS LOW DISEASE ACTIVITY STATE IN PATIENTS WITH NEWLY DIAGNOSED VERSUS ESTABLISHED SLE - A MULTICENTRE PROSPECTIVE STUDY

Background

Lupus low disease activity state (LLDAS) attainment has been reported to be associated with reduced damage accrual, flare, and mortality, as well as improved quality of life, in cohorts of SLE patients with established disease. Whether these associations are present in recent-onset disease is less well known.

Objectives

To evaluate the associations of LLDAS attainment with outcomes in patients with recent onset SLE.

Methods

Data from a 13-country longitudinal SLE cohort (ACR/SLICC criteria) were collected prospectively between 2013 and 2020 using standard templates. Organ damage and flare were captured using SLICC Damage Index and SELENA-SLEDAI Flare Index, respectively. LLDAS was defined as Golder et al., 2019 [1]. An inception cohort was defined based on duration since SLE diagnosis<1 year at enrolment. Patient characteristics between inception and non-inception cohorts were compared using Wilcoxon rank-sum (continuous variables) or Pearson’s Chi-squared tests (categorical variables). Survival analyses were performed to examine the association between LLDAS attainment and damage accrual and flare.

Results

The study cohort included 4,106 patients of whom 680 (16%) were recruited within 1 year of SLE diagnosis (inception cohort). Compared to the non-inception cohort, inception cohort patients were significantly younger, had higher disease activity (SLEDAI-2K and physician global assessment), used more glucocorticoids and immunosuppressants but had less organ damage at enrolment and only 88 (13.6%) patients accrued damage during a median 2.2 years follow-up (Table 1).

Table 1.Non-inception cohortInception cohortp-valuen=3426n=680Age at enrolment (years), median [IQR]40 [31, 51]33 [25, 44]<0.001Age at diagnosis (years), median [IQR]28 [21, 38]33 [25, 43]<0.001SLE duration at enrolment (years), median [IQR]10 [5, 16]1 [0, 1]<0.001Study duration (years), median [IQR]2.5 [1.0, 5.4]2.2 [0.9, 3.7]<0.001Females, n (%)3155 (92.1%)623 (91.6%)0.68Asian ethnicity, n (%)3037 (89.1%)595 (88.1%)0.49Prednisolone (PNL) use - ever, n (%)2865 (83.6%)620 (91.2%)<0.001Time adjusted mean (TAM)-PNL, median [IQR]5.0 [2.2, 8.6]6.2 [3.2, 10.3]<0.001Cumulative PNL (g), median [IQR]3.4 [0.5, 9.7]3.8 [1.1, 8.5]0.26Anti-Malarial use - ever, n (%)2669 (77.9%)569 (83.7%)<0.001Immunosupressant use -ever, n (%)2367 (69.1%)521 (76.6%)<0.001AMS (TAM-SLEDAI-2K), median [IQR]2.8 [1.2, 4.6]3.1 [1.6, 5.0]0.002TAM-PGA, median [IQR]0.4 [0.2, 0.7]0.4 [0.3, 0.8]<0.001Mild/moderate/severe flare ever, n (%)1789 (52.2%)391 (57.5%)0.012Organ damage accrual, n (%)629 (20.8%)88 (13.6%)<0.001LLDAS at baseline, n (%)1730 (50.5%)195 (28.7%)<0.001LLDAS-ever (at least once), n (%)2637 (78.2%)492 (73.9%)0.014≥50% time in LLDAS (LLDAS-5), n (%)1612 (50.6%)256 (41.1%)<0.001

Significantly fewer inception cohort patients were in LLDAS at enrolment than the non-inception cohort (29% vs. 51%, p<0.001). However, 74% of inception and 78% of non-inception cohort patients achieved LLDAS at least once during follow-up. Limiting analysis only to patients not in LLDAS at enrolment, time to first LLDAS attainment was assessed: inception cohort patients were 60% more likely to attain their first LLDAS (HR = 1.60 (95%CI: 1.40, 1.82), p<0.001) than non-inception cohort patients. LLDAS attainment was significantly protective against flare in the inception (HR, 95% CI) and non-inception (HR, 95% CI) cohorts. Trends towards protection against damage accrual in association with LLDAS in the inception cohort were not significant.

Conclusion

LLDAS attainment is protective from flare in recent onset SLE. Significant protection from damage accrual was not observed, due to low rates of damage accrual in the first years after SLE diagnosis.

References

[1]Golder, V., et al., Lupus low disease activity state as a treatment endpoint for systemic lupus erythematosus: a prospective validation study. The Lancet Rheumatology, 2019. 1(2): p. e95-e102.

Acknowledgements

We thank all patients participating in the Asia Pacific Lupus Collaboration (APLC) cohort, and all data collectors for their ongoing support for APLC research activities.

The APLC has received unrestricted project grants from AstraZeneca, BMS, Eli Lily, Janssen, Merck Serono, and UCB to support data collection contributing to this work.

Disclosure of Interests

Vera Golder: None declared, Rangi Kandane-Rathnayake: None declared, Worawit Louthrenoo: None declared, Yi-Hsing Chen Speakers bureau: Pfizer, Novartis, Abbvie, Johnson & Johnson, BMS, Roche, Lilly, GSK, Astra& Zeneca, Sanofi, MSD, Guigai, Astellas, Inova Diagnostics, UCB, Agnitio Science Technology, United Biopharma, Thermo Fisher, Consultant of: Pfizer, Novartis, Abbvie, Johnson & Johnson, BMS, Roche, Lilly, GSK, Astra and Zeneca, Sanofi, Guigai, Astellas, Inova Diagnostics, UCB, Agnitio Science Technology, United Biopharma, Thermo Fisher, Gilead, Grant/research support from: Yes. Clinical trials and/or research grants from Pfizer, Norvatis, BMS, Abbevie, Johnson & Johnson, Roche,Sanofi, Guigai, Roche, Boehringer Ingelheim, UCB, MSD, Astra-Zeneca,Astellas, Gilead, Jiacai Cho: None declared, Aisha Lateef: None declared, Laniyati Hamijoyo Speakers bureau: Pfizer, Novartis, Abbot, Shue Fen Luo: None declared, Yeong-Jian Jan Wu Speakers bureau: Pfizer, Lilly, Novartis, Abbvie, Sandra Navarra Speakers bureau: Pfizer, Johnson & Johnson, Novartis, Astellas, Grant/research support from: Astellas, Johnson & Johnson, Leonid Zamora: None declared, Zhanguo Li Speakers bureau: Eli, Lilly, Novartis, GSK, AbbVie, Paid instructor for: Pfizer, Roche, Johnson, Consultant of: Lilly, Pfizer, Grant/research support from: Pfizer, Yuan An: None declared, Sargunan Sockalingam Speakers bureau: Yes. Pfizer, Roche, Novartis, Grant/research support from: Roche and Novartis, Yasuhiro Katsumata Speakers bureau: Chugai Pharmaceutical Co., Ltd., Glaxo-Smithkline K.K., and Sanofi K.K., Masayoshi Harigai Speakers bureau: MH has received speaker’s fee from AbbVie Japan GK, Ayumi Pharmaceutical Co., Boehringer Ingelheim Japan, Inc.,Bristol Myers Squibb Co., Ltd., Chugai Pharmaceutical Co., Ltd., Eisai Co., Ltd., Eli Lilly Japan K.K., GlaxoSmithKline K.K., Kissei Pharmaceutical Co., Ltd., Pfizer Japan Inc., Takeda Pharmaceutical Co., Ltd., and Teijin Pharma Ltd, Consultant of: MH is a consultant for AbbVie, Boehringer-ingelheim, Bristol Myers Squibb Co., Kissei Pharmaceutical Co.,Ltd. and Teijin Pharma., Grant/research support from: MH has received research grants from AbbVie Japan GK, Asahi Kasei Corp., Astellas Pharma Inc., Ayumi Pharmaceutical Co., Bristol Myers Squibb Co., Ltd., Chugai Pharmaceutical Co., Daiichi-Sankyo, Inc.,Eisai Co., Ltd., Kissei Pharmaceutical Co., Ltd., Mitsubishi Tanabe Pharma Co., Nippon Kayaku Co., Ltd., Sekiui Medical, Shionogi & Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Co., Ltd., and Teijin Pharma Ltd., Yanjie Hao: None declared, Zhuoli Zhang Speakers bureau: Norvatis, GSK, Pfizer, BMDB Basnayake: None declared, Madelynn Chan Speakers bureau: AbbVie, Novartis, Consultant of: Advisory Board member for Pfizer, Eli-Lilly, Jun Kikuchi: None declared, Tsutomu Takeuchi Speakers bureau: AbbVie AYUMI Pharmaceutical Corp. Bristol-Myers Squibb Chugai Pharmaceutical Co, Ltd. Daiichi Sankyo Co., Ltd. Eisai Co., Ltd. Eli Lilly Japan, Gilead Sciences, Inc. Mitsubishi-Tanabe Pharma Corp. Pfizer Japan Inc. Sanofi K.K., Consultant of: Astellas Pharma, Inc. Chugai Pharmaceutical Co, Ltd. Eli Lilly Japan, Mitsubishi-Tanabe Pharma Corp., Grant/research support from: AbbVie Asahikasei Pharma Corp. Chugai Pharmaceutical Co, Ltd. Mitsubishi-Tanabe Pharma Corp. Sanofi K.K, Sang-Cheol Bae: None declared, Sean O’Neill Paid instructor for: Advisory board member for GSK, Fiona Goldblatt: None declared, Shereen Oon: None declared, Kathryn Gibson Speakers bureau: UCB, Consultant of: Novartis – co-chair for NSW and steering committee member for ARISE meeting Feb 2021

Janssen Pharmaceuticals – advisory board, Grant/research support from: Novartis, Employee of: Eli Lilly, Kristine Ng Speakers bureau: speaker fees and advisory board (Abbvie, Novartis, Janssen), Annie Law: None declared, Nicola Tugnet: None declared, Sunil Kumar: None declared, Cherica Tee: None declared, Michael Tee: None declared, Yoshiya Tanaka Speakers bureau: Daiichi-Sankyo, Eli Lilly, Novartis, YL Biologics, Bristol-Myers, Eisai, Chugai, Abbvie, Astellas, Pfizer, Sanofi, Asahi-kasei, GSK, Mitsubishi-Tanabe, Gilead, Janssen, Grant/research support from: Daiichi-Sankyo, Eli Lilly, Novartis, YL Biologics, Bristol-Myers, Eisai, Chugai, Abbvie, Astellas, Pfizer, Sanofi, Asahi-kasei, GSK, Mitsubishi-Tanabe, Gilead, Janssen, C.S. Lau Shareholder of: Pfizer, Sanofi and Janssen, Mandana Nikpour Speakers bureau: Actelion, GSK, Janssen, Pfizer, UCB, Paid instructor for: UCB, Consultant of: Actelion, Boehringer Ingelheim, Certa Therapeutics, Eli Lilly, GSK, Janssen, Pfizer, UCB, Grant/research support from: Actelion, Astra Zeneca, BMS, GSK, Janssen, UCB, Alberta Hoi Consultant of: AH is on the advisory board for Abbvie and GSK, Grant/research support from: AH has received research support from AstraZeneca, GSK, BMS, Janssen, and Merck Serono, Eric F. Morand Speakers bureau: AstraZeneca, Paid instructor for: Eli Lilly, Consultant of: AstraZeneca, Amgen, Biogen, BristolMyersSquibb, Eli Lilly, EMD Serono, Genentech, Janssen, Grant/research support from: AstraZeneca, BristolMyersSquibb, Eli Lilly, EMD Serono, Janssen

Photodynamique therapy relieves tumor vascular anergy and promotes immune cell trafficking in an orthotopic mouse model of malignant pleural mesothelioma

Objective

Malignant pleural mesothelioma (MPM) is a deadly disease with limited treatment options. Recently, dual immune checkpoint inhibition therapy (ICI) showed improved patient survival. However, only a fraction of patients were responsive to immunotherapy. One potential mechanism of MPM resistance to ICIs could be their endothelial anergy that hampers leukocyte trafficking to the tumor bulk. Here, we hypothesized that vascular-targeted low dose photodynamic therapy (L-PDT), treatment of MPM could relieve tumor endothelial anergy and improve immunotherapy efficacy.

Methods

Using an orthotopic syngeneic MPM murine model (AB12 cells injected in the pleura of BALB/c mice), we determined the impact of L-PDT on the endothelial expression of E-Selectin, a key molecule involved in leukocyte diapedesis by immunohistochemistry. Furthermore, to confirm the role of E-selectin, we determined the extravasation of effector T cells (CD8+/CD4+) by immunostaining in L-PDT treated tumors in the presence or absence of an E-selectin blocking antibody. Finally, we assessed tumor growth/survival of our MPM murine model treated with L-PDT alone or combined to ICIs.

Results

L-PDT pre-treatment enhanced MPM endothelial E-Selectin expression in vivo. The latter was associated with increased CD4+ and CD8+ lymphocyte infiltration of MPM following L-PDT which did not occur after E-Selectin blockade. Also, L-PDT pre-treatment of MPM influenced favorably tumor control, mouse survival and the impact of ICIs compared to controls.

Conclusion

L-PDT pre-treatment relieves endothelial anergy in MPM which improves antitumor immunity and response to ICI. This approach could constitute a promising pre-treatment option, in combination with ICIs, for the management of this deadly disease.

Improvement of IMRT QA prediction using imaging-based neural architecture search

PURPOSE

Machine learning has been used to predict the gamma passing rate of Intensity-modulated radiation therapy (IMRT) QA results. In this work, we applied a novel neural architecture search to automatically tune and search for the best deep neural networks instead of using hand-designed deep learning architectures.

METHOD AND MATERIALS

One hundred and eighty-two IMRT plans were created and delivered with portal dosimetry. A total of 1497 fields for multiple treatment sites were delivered and measured by portal imagers. Gamma criteria of 2%/2mm with a 5% threshold were used. Fluence maps calculated for each plan were used as inputs to a convolution neural network (CNN). Auto-Keras was implemented to search for the best CNN architecture for fluence image regression. The network morphism was adopted in the searching process, in which the base models were ResNet and DenseNet. The performance of this CNN approach was compared with tree-based machine learning models previously developed for this application, using the same data set.

RESULTS

The deep-learning-based approach had 98.3% of predictions within 3% of the measured 2%/2mm gamma passing rates with a maximum error of 3.1% and a mean absolute error of less than 1%. Our results show that this novel architecture search approach achieves comparable performance to the machine-learning-based approaches with handcrafted features.

CONCLUSIONS

We implemented a novel CNN model using imaging-based neural architecture for IMRT QA prediction. The imaging-based deep-learning method does not require manual extraction of relevant features and is able to automatically select the best network architecture. This article is protected by copyright. All rights reserved.

Highly efficient CRISPR-Cas9-mediated editing identifies novel mechanosensitive microRNA-140 targets in primary human articular chondrocytes

OBJECTIVE

MicroRNA 140 (miR-140) is a chondrocyte-specific endogenous gene regulator implicated in osteoarthritis (OA). As mechanical injury is a primary aetiological factor in OA, we investigated miR-140-dependent mechanosensitive gene regulation using a novel CRISPR-Cas9 methodology in primary human chondrocytes.

METHOD

Primary (passage 1/2) human OA chondrocytes were isolated from arthroplasty samples (six donors) and transfected with ribonuclear protein complexes or plasmids using single guide RNAs (sgRNAs) targeting miR-140, in combination with Cas9 endonuclease. Combinations of sgRNAs and single/double transfections were tested. Gene editing was measured by T7 endonuclease 1 (T7E1) assay. miRNA levels were confirmed by qPCR in chondrocytes and in wild type murine femoral head cartilage after acute injury. Predicted close match off-targets were examined. Mechanosensitive miR-140 target validation was assessed in 42 injury-associated genes using TaqMan Microfluidic cards in targeted and donor-matched control chondrocytes. Identified targets were examined in RNAseq data from costal chondrocytes from miR-140^-/- mice.

RESULTS

High efficiency gene editing of miR-140 (90-98%) was obtained when two sgRNAs were combined with double RNP-mediated CRISPR-Cas9 transfection. miR-140 levels fell rapidly after femoral cartilage injury. Of the top eight miR-140 gene targets identified (P < 0.01), we validated three previously identified ones (septin 2, bone morphogenetic protein 2 and fibroblast growth factor 2). Novel targets included Agrin, a newly recognised pro-regenerative cartilage agent, and proteins associated with retinoic acid signalling and the primary cilium.

CONCLUSION

We describe a highly efficient CRISPR-Cas9-mediated strategy for gene editing in primary human chondrocytes and identify several novel mechanosensitive miR-140 targets of disease relevance.

A reconstruction approach for proton computed tomography by modeling the integral depth dose of the scanning proton pencil beam

PURPOSE

To present a proton computed tomography (pCT) reconstruction approach that models the integral depth dose (IDD) of the clinical scanning proton beam into beamlets. Using a multi-layer ionization chamber (MLIC) as the imager, the proposed pCT system and the reconstruction approach can minimize the extra ambient neutron dose and simplify the beamline design by eliminating an additional collimator to confine the proton beam.

METHODS

Monte Carlo simulation was applied to digitally simulate the IDDs of the exiting proton beams detected by the MLIC. A forward model was developed to model each IDD into the weighted sum of percentage depth doses (PDDs) of the constituent beamlets separated laterally by 1mm. The water equivalent path lengths (WEPLs) of the beamlets were determined by iteratively minimizing the squared L2-norm of the forward projected and simulated IDDs. The final WEPL values were reconstructed to pCT images, i.e., proton Stopping Power Ratio (SPR) maps, through simultaneous algebraic reconstruction technique with total variation regularization (SART-TV). The reconstruction process was tested with a digital cylindrical water-based phantom and an ICRP adult reference computational phantom. The mean of SPR within regions of interest (ROIs) and the WEPLs along 4 mm-wide beams (WEPL_4mm ) were compared to the reference values. The spatial resolution was analyzed at the edge of a cortical insert of the cylindrical phantom.

RESULTS

The percentage deviations from reference SPR were within ±1% in all selected ROIs. The mean absolute error of the reconstructed SPR was 0.33%, 0.19%, and 0.27% for the cylindrical phantom, the adult phantom at the head and lung region, respectively. The corresponding percentage deviations from reference WEPL_4mm were 0.48%±0.64%, 0.28% ± 0.48%, and 0.22% ± 0.49%. The full width at half maximum (FWHM) of the line spread function (LSF) derived from the radial edge spread function (ESF) of a cortical insert was 0.13 cm. The frequency at 10% of the modulation transfer function (MTF) was 6.38 cm^-1 . The mean signal-to-noise ratio (SNR) of all the inserts was 2.45. The mean imaging dose was 0.29 cGy and 0.25 cGy at the head and lung region of the adult phantom, respectively.

CONCLUSION

A new pCT reconstruction approach was developed by modeling the IDDs of the uncollimated scanning proton beams in the pencil beam geometry. SPR accuracy within ±1%, spatial resolution of better than 2mm at 10% MTF, and imaging dose at the magnitude of mGy were achieved. Potential side effects caused by neutron dose were eliminated by removing the extra beam collimator. This article is protected by copyright. All rights reserved.

[The molecular mechanism of oxaliplatin-induced peripheral neuropathic pain]

Objective: To investigate the molecular mechanism of oxaliplatin-induced chemotherapy-induced peripheral neuropathic pain (CIPNP). Methods: A total of 16 male Sprague-Dawley rats of specific pathogen-free grade were randomly divided into two groups: oxaliplatin experimental group (2.4 mg/kg oxaliplatin dissolved in 5.0% glucose solution, n=8) and control group (equal volume 5% glucose solution, n=8). The rat model of CIPNP was established by continuous administration with oxaliplatin. In addition, mechanical allodynia, thermal hyperalgesia and cold hyperalgesia were measured and compared between the two groups. To explore the molecular mechanism of oxaliplatin-induced CIPNP, the gene expression of dorsal root ganglia (DRG) from the rat model of CIPNP was analyzed using RNA sequencing (RNA-Seq). Results: Mechanical and thermal hypersensitivity was exhibited on day 7 and a stronger hypersensitivity was observed on day 14. A total of 20 152 genes were quantified by RNA-Seq, and 379 differentially expressed genes (DEGs) were obtained with absolute fold change cut-offs ≥ 2 and P value<0.05. There were 7 genes (Npy, Car3, Cdkn1a, Nts, Prc1, Ms4a7 and Ecel1) that were involved in peripheral nerve injury-related neuropathic pain. Gene ontology (GO) functional enrichment analyses indicated that the DEGs induced by oxaliplatin were involved in oxygen transport, cell division, intermediate, centromere, oxygen transporter activity, oxygen binding. Moreover, the result of Kyoto Encyclopedia of genes and genomes (KEGG) analyses highlighted that the DEGs induced by oxaliplatin were involved in malaria, African trypanosomiasis, primary immunodeficiency, peroxisome proliferator activated receptor (PPAR) signaling pathway. Conclusion: Oxaliplatin induces CIPNP via pain-related genes and signaling pathways.

[Application of the enhanced milieu teaching model in language intervention of children with language developmental delay in outpatient child healthcare clinic]

Objective: To explore the role of the enhanced milieu teaching (EMT) model in early intervention of children with language developmental delay (LDD) in outpatient child healthcare clinic. Methods: Case-control study design was adopted. Twenty-eight children aged 2.5 to 4.0 years who were diagnosed with LDD from June 2019 to June 2020 at the Division of Child Healthcare, Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology were recruited as the intervention group, and participated in one-on-one EMT model language rehabilitation sessions for 3 months (12 sessions). Another 27 children with LDD who attended the Division of Child Healthcare around the same period of time were recruited as control group, all of whom did not attend any types of language intervention in the subsequent three months. Both groups were followed up three months later. Gesell developmental scale (GDS) and diagnostic receptive and expressive assessment of Mandarin-comprehensive (DREAM-C) standardized language test were used to evaluate and compare children's development level at the first and follow-up visit, with the treatment effect of the EMT model being evaluated with independent sample t-test. Results: The language development quotient of GDS of the intervention group (22 boys and 6 girls) at the follow-up visit was significantly higher than that of at the first visit (64±21 vs. 52±17,t=4.960, P<0.01). The Dream-C test scores of total language (89±16 vs. 77±14, t=5.061, P<0.01), receptive language (90±16 vs. 77±15, t=5.301, P<0.01), semantics (93±20 vs. 79±19, t=5.06, P<0.01), and syntax after training (84±14 vs. 76±11, t=3.209, P<0.01) were significantly higher than those at the first visit. In the control group (19 boys and 8 girls), the only improvement was found in the Dream-C semantics score (82±26 vs. 71±18, t=2.330, P<0.05). There was no significant difference in any domains in GDS at the first and follow-up visit (all P>0.05). Conclusions: Early language rehabilitation training based on the EMT model has a significant effect on all domains of language development for children with LDD. Therefore, EMT model is a language intervention model compatible in the child healthcare outpatient clinic settings.

Tetrahedron beam imaging with a multi-pixel thermionic emission X-ray source and a photon-counting detector: A benchtop experimental study

PURPOSE

A tetrahedron beam (TB) X-ray system with a linear X-ray source array and a linear detector array positioned orthogonal to each other may overcome the X-ray scattering problem of traditional cone-beam X-ray systems. We developed a TB imaging benchtop system using a linear array X-ray source to demonstrate the principle and benefits of TB imaging.

METHODS

A multi-pixel thermionic emission X-ray (MPTEX) source with 48 focal spots in 4-mm spacing was developed in-house. The X-ray beams are collimated to a stack of fan beams that are converged to a 6-mm wide multi-row photon-counting detector (PCD). The data collected with a sequential scan of the sources at a fixed view angle were synthesized to a 2D radiography image by a shift-and-add algorithm. The data collected with a full rotation of the system were reconstructed into 3D TB CT (TBCT) images using an Feldkamp, Davis, and Kress (FDK)-based computed tomography (CT) algorithm modified for the TB geometry.

RESULTS

With an 18.8-cm long source array and a 35-cm long detector array, the TB benchtop system provides a 25-cm cross-sectional and 8-cm axial field of view (FOV). The scatter-to-primary ratio (SPR) was approximately 17% for TB, as compared with 120% for cone beam geometry. The TBCT system enables reconstructions in two-dimensional radiography and three-dimensional volumetric CT. The TBCT images were free of "cupping" artifacts and have similar image quality as diagnostic helical CT.

CONCLUSIONS

A TB imaging benchtop imaging system was successfully developed with MPTEX source and PCD. Phantom and animal cadaver imaging demonstrated that the TB system can produce satisfactory radiographic X-ray images and 3D CT images with image quality comparable to diagnostic helical CTs.