Observation of the γγ→ττ Process in Pb+Pb Collisions and Constraints on the τ-Lepton Anomalous Magnetic Moment with the ATLAS Detector

This Letter reports the observation of τ-lepton-pair production in ultraperipheral lead-lead collisions Pb+Pb→Pb(γγ→ττ)Pb and constraints on the τ-lepton anomalous magnetic moment a_{τ}. The dataset corresponds to an integrated luminosity of 1.44  nb^{-1} of LHC Pb+Pb collisions at sqrt[s_{NN}]=5.02  TeV recorded by the ATLAS experiment in 2018. Selected events contain one muon from a τ-lepton decay, an electron or charged-particle track(s) from the other τ-lepton decay, little additional central-detector activity, and no forward neutrons. The γγ→ττ process is observed in Pb+Pb collisions with a significance exceeding 5 standard deviations and a signal strength of μ_{ττ}=1.03_{-0.05}^{+0.06} assuming the standard model value for a_{τ}. To measure a_{τ}, a template fit to the muon transverse-momentum distribution from τ-lepton candidates is performed, using a dimuon (γγ→μμ) control sample to constrain systematic uncertainties. The observed 95% confidence-level interval for a_{τ} is -0.057 Collapse

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Measurement of Ultra-High-Energy Diffuse Gamma-Ray Emission of the Galactic Plane from 10 TeV to 1 PeV with LHAASO-KM2A

The diffuse Galactic γ-ray emission, mainly produced via interactions between cosmic rays and the interstellar medium and/or radiation field, is a very important probe of the distribution, propagation, and interaction of cosmic rays in the Milky Way. In this Letter, we report the measurements of diffuse γ rays from the Galactic plane between 10 TeV and 1 PeV energies, with the square kilometer array of the Large High Altitude Air Shower Observatory (LHAASO). Diffuse emissions from the inner (15°10  TeV). The energy spectrum in the inner Galaxy regions can be described by a power-law function with an index of -2.99±0.04, which is different from the curved spectrum as expected from hadronic interactions between locally measured cosmic rays and the line-of-sight integrated gas content. Furthermore, the measured flux is higher by a factor of ∼3 than the prediction. A similar spectrum with an index of -2.99±0.07 is found in the outer Galaxy region, and the absolute flux for 10≲E≲60  TeV is again higher than the prediction for hadronic cosmic ray interactions. The latitude distributions of the diffuse emission are consistent with the gas distribution, while the longitude distributions show clear deviation from the gas distribution. The LHAASO measurements imply that either additional emission sources exist or cosmic ray intensities have spatial variations.

A Comparison of Clinicopathologic Outcomes and Patterns of Lymphatic Spread across Neoadjuvant Chemotherapy, Neoadjuvant Chemoradiotherapy and Neoadjuvant Immunochemotherapy in Locally Advanced Esophageal Squamous Cell Carcinoma

PURPOSE/OBJECTIVE(S)

To evaluate the differences in pathologic complete response (pCR) rates, TRG score, pathologic T stage and the pattern of lymphatic spread among patients receiving neoadjuvant chemotherapy (NCT) or neoadjuvant chemoradiotherapy (NCRT) or neoadjuvant immunochemotherapy (NICT) prior to esophagectomy for locally advanced esophageal squamous cell carcinoma (ESCC).

MATERIALS/METHODS

A total of 702 patients with ESCC who completed transthoracic esophagectomy followed neoadjuvant therapy at three cancer centers from January 2017 to December 2022 were enrolled. Among the included patients, 382 patients were treated with NCR, 172 with NCRT, and 148 with NICT. Inverse probability of treatment weighting (IPTW) was performed to control potential confounding factors. Pathological response of primary tumor was evaluated using the Chirieac modified tumor regression grade (TRG) system. The complete regression of primary lesion and nodal metastases were considered pCR. Lymph node classification system used the 8th edition of AJCC. Specimens were assessed for pattern of lymphatic spread.

RESULTS

After adjusting for baseline characteristics, the R0 resection rate did not significantly differ between the patients receiving NCT or NCRT or NICT (99.48% vs.100% vs.98.65%, P = 0.273). Compared with the NCT group, the NCRT group and NICT group had an advantage in pathological response (P<0.05). The pCR rate was 7.07% in the NCT group, 30.23% in the NCRT group, and 22.30% in the NICT group. Compared to the other two groups, the TRG score (P<0.05) and pathologic T stage (P<0.05) in the NCT group were significantly higher. In the NCT group, 9.97% had ypT0 disease, compared with 35.76% in the NCRT group and 25.68% in the NICT group. And in the NCT group, 9.71% had TRG1 disease, compared with 32.76% in the NCRT group and 25% in the NICT group. Compared with NICT, NCRT can significantly reduce the rate of LNM in station 1R (0 vs 3.38%, P<0.05) and 2R (1.15% vs 6.76%, P<0.05). Subgroup analysis according to the tumor location distribution showed that in upper thoracic cases, there was no statistical difference in LNM rates among stations no matter whether patients received NCT or NCRT or NICT. NICT group had higher LNM rates in station 2R (9.1%) in middle thoracic cases (P<0.05) and in station 18 (7.5%) (P<0.05) in lower thoracic cases, compared with the NCRT group and NCT group.

CONCLUSION

NCRT or NICT followed by surgery may result in a promising pCR rate and show a better performance in therapeutic response of primary lesion. No matter whether patients received NCT or NCRT or NICT, multiple level and skip node metastases are common, and adequate lymphadenectomy should be achieved to ensure the complete removal of metastatic lymph nodes.

Application of a Contralateral Esophageal-Sparing Technique to Reduce Radiation Esophagitis in Limited-Stage Small Cell Lung Cancer Treated with Twice-Daily Radiotherapy and Concurrent Chemotherapy

PURPOSE/OBJECTIVE(S)

Acute esophagitis (AE) is a common radiation-related toxicity after concurrent twice-daily hyperfractionated radiotherapy and chemotherapy in limited-stage small cell lung cancer (LS-SCLC) patients, which could limit dose-escalation of the target and make treatment postponed to decrease local tumor control. More esophageal protective techniques should be proposed to reduce radiation severe esophagitis of LS-SCLC patients.

MATERIALS/METHODS

We retrospectively applied a contralateral esophagus sparing technique (CEST) in 20 unresectable LS-SCLC patients, who had gross tumor within 1 cm of the esophagus and received a total dose of 45 Gy of concurrent twice-daily radiation and standard chemotherapy regimen. The contralateral esophagus (CE) was contoured as an avoidance structure, and the feasibility of CEST on promoting a steep dose falloff beyond the target volume near esophagus was analyzed. The appropriate dose constraints of CE were also investigated. The AE events were recorded according to the RTOG acute toxicity grading system.

RESULTS

We performed CEST in 20 LS-SCLC consecutive patients, among whom three patients experienced severe AE after concurrent chemoradiotherapy. Each treatment plan of eligible patients assured high radiation doses delivering, with the planning and gross tumor volume covered by 95% and 100% of the prescription dose. Among these patients, the median maximum esophagus dose declined from 47.9 Gy (range, 46.6-49.7 Gy) to 41.3 Gy (range, 35.9-48.2 Gy), as well as V30 and V36 of esophagus decreased from 9.22 Gy (range, 0.42-17.71 Gy) and 7.39 Gy (range, 0-16.19 Gy) to 2.40 Gy (range, 0-5.68 Gy) and 0.53 Gy (range, 0 -2.69 Gy) after CEST applying, respectively (all p<0.001). The CE's median maximum dose, V30, and V36 were 41.3 Gy, 2.13 cc, and 0.24 cc, respectively.

CONCLUSION

By using proposed CE dose constraints of Dmax≤42 Gy, V30 ≤3.5 cc and V36 ≤0.5 cc, we confirmed the feasibility and efficacy of CEST to avoid exposing the esophagus cross-section to high prescription doses in LS-SCLC patients receiving twice-daily hyperfractionated IMRT and concurrent chemotherapy. These findings support the clinical practice of CEST in LS-SCLC patients, while more prospective and large-scale studies are warranted.

Novel Deep Learning Segmentation Models for Accurate GTV and OAR Segmentation in MR-Guided Adaptive Radiotherapy for Pancreatic Cancer Patients

PURPOSE/OBJECTIVE(S)

MR-guided adaptive radiotherapy (MRgART) improves target coverage and organ-at-risk (OAR) sparing in pancreatic cancer radiation therapy (RT). Inter-fractional changes in patients undergoing RT require time intensive re-delineation of gross tumor volume (GTV) and OARs prior to adaptive optimization. Accurate automatic segmentation has the potential to significantly improve efficiency of the adaptive workflow. We hypothesized that state-of-the-art deep learning (DL) segmentation models could adequately segment GTV and OARs in both planning and daily fractional MR scans.

MATERIALS/METHODS

The study included 21 patients with pancreatic cancer treated with MRgART (10 Gy x 5 fractions). The planning MR as well as all daily MR images and registrations were collected (6 image sets per patient and a total of 126 image sets). The planning MR and fraction 1-4 image sets were used as the training set (N = 105), while the test set (N = 21) comprised images for fraction 5, to simulate the last step of incremental learning from planning to final fraction. Evaluated contours included the GTV, Small Bowel, Large Bowel, Duodenum, Left and Right Kidney, Liver, Spinal Cord, and Stomach. To mimic clinical conditions, contour accuracy was evaluated within the ring structure surrounding the PTV, inside of which daily adaptive re-contouring is applied (2 cm expansion in the cradio-caudal direction, 3 cm expansion otherwise). We evaluated three DL model architectures: SegResNet, SegResNet 2D, and SwinUNETR to autosegment GTV and OARs. The segmentation models were trained on the training set using 5-fold cross-validation (CV) and quantitatively analyzed by comparing against clinically used contours with DICE scores. Qualitative analysis was performed by a radiation oncologist using a scoring scale: 1 = perfect, 2 = minor discrepancy, 3 = moderate discrepancy, and 4 = rejected.

RESULTS

Overall, the DL segmentations were in acceptable agreement with clinical contours. The best performing model was the SwinUNETR model with overall training DICE = 0.88±0.06, test DICE = 0.78±0.11, and qualitative score of 1.6±0.8. The agreement between the DL model and clinical segmentation for the GTV was 0.79±0.08, with a qualitative score of 2.2±0.9. The highest and lowest OAR DICE scores were for the Left Kidney (DICE = 0.93) and Small Bowel (DICE = 0.68), respectively. The highest qualitative OAR scores were for the Kidney, Liver, and Spinal Cord (score = 1.0) and the lowest qualitative score was for the Duodenum (score = 2.3) CONCLUSION: We report here the most comprehensive work on DL segmentation for pancreatic cancer MRgART, including quantitative and clinically-pertinent qualitative evaluations of 126 image sets and 3 DL architectures. Our data show good quantitative agreement between DL and clinical contours, and acceptable clinician evaluations for the majority of GTVs and OARs. The current work has great potential to significantly reduce a major bottleneck in the MRgART workflow for pancreatic cancer patients.

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.

SEA-Net: Structure-Enhanced Attention Network for Limited-Angle CBCT Reconstruction of Clinical Projection Data

PURPOSE/OBJECTIVE(S)

Limited-angle CBCT (LA-CBCT) is of great clinical interest, because the scanning time and the patient dose are proportional to the scanning range of gantry rotation angles of CBCT. However, the image reconstruction for LA-CBCT remains technically challenging, which suffers from severe wedge artifacts and image distortions. This work aims to improve LA-CBCT by developing deep learning (DL) methods for real clinical CBCT projection data, which is the first feasibility study of clinical-projection-data-based LA-CBCT, to the best of our knowledge.

MATERIALS/METHODS

Targeting at real clinical projection data, we have explored various DL methods such as image/data/hybrid-domain methods and finally developed a so-called Structure-Enhanced Attention Network (SEA-Net) method that has the best image quality from clinical projection data among the DL methods we have implemented. Specifically, the proposed SEA-Net employs a specialized structure enhancement sub-network to promote texture preservation. Based on the observation that the distribution of wedge artifacts in reconstruction images is non-uniform, the spatial attention module is utilized to emphasize the relevant regions while ignores the irrelevant ones, which leads to more accurate texture restoration.

RESULTS

SEA-Net was validated in comparison with analytic (FDK), iterative (TV), image-domain DL (DDNet and FED-INet, data-domain DL (DCAR), dual-domain DL (Sam'Net), and various unrolling DL (hdNet, CTNet, FSR-Net, CasRedSCAN) methods. Among all methods, the SEA-Net had the best image reconstruction quality as quantified by root-mean-square error (RMSE), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM), for various LA-CBCT problems of 90°-180° projection data. In addition, LA-CBCT via SEA-Net provided comparable accuracy for both patient setup (quantified by image registration accuracy from planning CT (pCT) to CBCT) and dose calculation (see the table), with full-view CBCT.

CONCLUSION

We explored various DL methods and developed an image-domain-based method termed SEA-Net that provided the best image quality for clinical projection data. To the best of our knowledge, this is the first feasibility study of the real clinical-projection-data-based LA-CBCT. Moreover, LA-CBCT via SEA-Net can potentially provide comparable accuracy for patient setup and dose calculation, with full-view CBCT.

Effect of artesunate on cardiovascular complications in periodontitis in a type I diabetes rat model and related mechanisms

PURPOSE

Both cardiovascular disease and periodontitis are complications of diabetes that have a great impact on human life and health. Our previous research found that artesunate can effectively improve cardiovascular disease in diabetes and has an inhibitory effect on periodontal disease. Therefore, the present study aimed to explore the potential therapeutic possibility of artesunate in the protection against cardiovascular complications in periodontitis with type I diabetes rats and to elucidate the possible underlying mechanisms.

METHODS

Sprague‒Dawley rats were randomly divided into the healthy, diabetic, periodontitis, diabetic with periodontitis, and artesunate treatment groups (10, 30, and 60 mg/kg, i.g.). After artesunate treatment, oral swabs were collected and used to determine changes in the oral flora. Micro-CT was performed to observe changes in alveolar bone. Blood samples were processed to measure various parameters, while cardiovascular tissues were evaluated by haematoxylin-eosin, Masson, Sirius red, and TUNEL staining to observe fibrosis and apoptosis. The protein and mRNA expression levels in the alveolar bone and cardiovascular tissues were detected using immunohistochemistry and RT‒PCR.

RESULTS

Diabetic rats with periodontitis and cardiovascular complications maintained heart and body weight but exhibited reduced blood glucose levels, and they were able to regulate blood lipid indicators at normal levels after artesunate treatment. The staining assays suggested that treatment with 60 mg/kg artesunate has a significant therapeutic effect on myocardial apoptotic fibrosis. The high expression of NF-κB, TLR4, VEGF, ICAM-1, p38 MAPK, TGF-β, Smad2, and MMP9 in the alveolar bone and cardiovascular tissue in the type I diabetes and type I diabetes with periodontitis rat models was reduced after treatment with artesunate in a concentration-dependent manner. Micro-CT showed that treatment with 60 mg/kg artesunate effectively alleviated alveolar bone resorption and density reduction. The sequencing results suggested that each model group of rats had vascular and oral flora dysbiosis, but artesunate treatment could correct the dysbacteriosis.

CONCLUSIONS

Periodontitis-related pathogenic bacteria cause dysbiosis of the oral and intravascular flora in type I diabetes and aggravate cardiovascular complications. The mechanism by which periodontitis aggravates cardiovascular complications involves the NF-κB pathway, which induces myocardial apoptosis, fibrosis, and vascular inflammation.

Inter-fractional Assessment during MR-guided Online Adaptive Radiotherapy for Glioblastoma

PURPOSE/OBJECTIVE(S)

Magnetic resonance image (MRI) guided radiation therapy has the potential to improve outcomes for glioblastoma by adapting to tumor changes during radiation therapy. This study aimed to assess the feasibility and potential benefits of MR-guided online adaptive radiotherapy (MRgOART) for patients with glioblastoma.

MATERIALS/METHODS

Twenty consecutive patients with glioblastoma were treated with MRgOART of 60 Gy in 30 fractions by the 1.5 T MR-Linac. The MRgOART fractions employed daily MR scans and the contours were utilized to create each adapted plan. The gross tumor volume (GTV) and clinical target volume (CTV) were delineated on MRI of pre-treatment simulation (Fx0) and all fractions (Fx1, Fx2, Fx3 ... Fx30) to evaluate the inter-fractional changes. These changes were quantified using absolute/relative volume (∆V), Dice similarity coefficient (DSC) and Hausdorff distance (HD) metrics. The reference treatment plans were generated using step-and-shoot IMRT and utilized 7-9 beam groups on original CT. Before the treatment, a synthetic CT (sCT) quality assurance (QA) process was performed to assess the dose accuracy of bulk relative electron density (rED) assignment for online MRI based treatment plan in terms of gamma analysis, point dose comparison and dose volume histogram (DVH) parameters. Then, the online adaptative treatment plans were obtained by re-optimizing based on the contours on daily pre-treatment MRI by "adapt to shape" workflow. Non-adaptive plans for each patient were generated by recalculating the dose from the reference plans on daily online MRI by "adapt to position" workflow. GTV and CTV coverage and organ at risk (OAR) constraints were used to compare non-adaptive and adaptive plans.

RESULTS

For both criteria, the 1%/1mm (98.58%±0.15%) and 2%/2mm (99.88%±0.18%) gamma passing rate results were always clinically acceptable in sCT QA process. The differences on point dose and DVH parameters between the plans based on sCT and original CT were less than 1%. A total of 20 patients with 600 fractions were evaluated. The results showed that large inter-fractional changes for GTV limited the efficacy of radiation therapy (DSC: 0.78±0.08, HD: 20.94±3.64mm, ∆V: 2.92%±6.36%). The inter-fractional CTV changes were smaller (DSC: 0.91±0.04, HD: 15.31±3.09mm, ∆V: 1.41%±1.29%). GTV coverage of non-adaptive plans was below the prescribed coverage in 228/600 fractions (38%), with 90 (15%) failing by more than 10%. For CTV coverage of non-adaptive plans, the changes were less than 5%. Online adaptative plans improved GTV and CTV coverage significantly (p<0.001) to 99%. The adaptive plans also had lower dose to whole brain than non-adaptive plans (p<0.001).

CONCLUSION

Significant inter-fractional tumor changes could be found during radiotherapy in patients with glioblastoma treated by the 1.5 T MR-Linac. Daily MR-guided re-optimization of treatment plans corrected for day-to-day anatomical variations and resulted in adequate target coverage in all fractions.

Delta-Radiomics Guides Adaptive De-Intensification after Induction Chemotherapy in Locoregionally Advanced Nasopharyngeal Carcinoma in the IMRT Era

PURPOSE/OBJECTIVE(S)

In the setting of intensity-modulated radiotherapy (IMRT) and induction chemotherapy (IC), the benefits from concurrent chemotherapy remained controversial for locoregionally advanced nasopharyngeal carcinoma (LANPC). This study aimed to construct a delta-radiomics model for benefit prediction and patient selection for omitting concurrent chemotherapy.

MATERIALS/METHODS

Between December 2009 and December 2015, a total of 718 patients with LANPC treated with IC+IMRT or IC+concurrent chemoradiotherapy (CCRT) were retrospectively enrolled and randomly assigned to a training set (n = 503) and a validation set (n = 215). Radiomic features were extracted from magnetic resonance images of pre-IC and post-IC. Interclass correlation coefficients and Pearson correlation coefficients were calculated to select robust radiomic features. After univariate Cox analysis, a delta-radiomics signature was built using the LASSO-Cox regression. A nomogram incorporating the delta-radiomics signature and clinical prognostic factors was then developed and evaluated for calibration and discrimination. Risk stratification by the nomogram was evaluated by Kaplan-Meier methods. The primary outcome was overall survival (OS).

RESULTS

The delta-radiomics signature, which comprised 19 selected features, was independently associated with prognosis. It yielded an area under the receiver operating characteristic curve (AUC) of 0.77 (95% confidence interval [CI] 0.71 to 0.82) for the training set and 0.71 (95% CI 0.61 to 0.81) for the validation set. The nomogram composed of the delta-radiomic signature, age, T category, N category, pre-treatment Epstein-Barr virus DNA, and treatment showed great calibration and discrimination performance with an AUC of 0.80 (95% CI 0.75 to 0.85) for the training set and 0.75 (95% CI 0.64 to 0.85) for the validation set. Risk stratification by the nomogram excluding the treatment variable resulted in two risk groups with distinct OS. Significant better outcomes were observed in the high-risk patients with IC+CCRT compared to those with IC+IMRT (5-year OS: 73.8% vs. 61.4% in the training set and 85.8% vs. 65.6% in the validation set; all log-rank p < 0.05), while comparable outcomes between IC+CCRT and IC+IMRT were shown for the low-risk patients (95.8% vs. 95.8% in the training set and 92.2% vs. 88.3% in the validation set; all log-rank p > 0.05).

CONCLUSION

The delta-radiomics signature was identified as an independent indicator of LANPC. Integrating clinical predictors with the delta-radiomics signature, the radiomics-based nomogram could predict individual's survival outcomes and benefits from concurrent chemotherapy after IC for LANPC. Low-risk patients with LANPC determined by the nomogram may be potential candidates for omission of concurrent chemotherapy following IC in the IMRT era.

Deep Learning-Based Esophageal Tumor Identification on CT Slice

PURPOSE/OBJECTIVE(S)

The study aims to use deep learning to improve the accuracy of identifying esophageal tumors on CT slices for radiotherapy planning. The identification of Gross Tumor Volume (GTV) can be challenging due to low contrast with surrounding tissue. Other methods like endoscopy and PET scan can provide additional information, but may not be suitable for radiotherapy due to differences in tissue density and alignment needs.

MATERIALS/METHODS

A multi-task deep learning network was developed, which perform both segmentation and slice classification, simultaneously. For segmentation, the normal esophagus and tumor were treated as a single structure due to the difficulty in distinguishing between them on CT images. The slices were divided into 3 categories, including tumor, normal esophageal and other. An Unet was used for segmentation and generate the mask to remove irrelevant areas. The masked image will be input into a Resnet to obtain the categories of slices. The performance of classification was accessed by ROC curve, AUC and confusion matrix on a new dataset and PET images.

RESULTS

The multi-task deep learning network was developed on a dataset of 315 patients' CT images and GTV segmentations, which were reviewed and verified by physicians. The model was then evaluated on an additional validation dataset of 30 patients, resulting in an accuracy of 88%. In terms of sensitivity and specificity, the model showed high performance, with a sensitivity of 97% and specificity of 95% for tumor and normal esophagus in the validation dataset. Meanwhile, the specificity was 85% and the specificity was 80% for tumor and normal esophagus in PET images dataset.

CONCLUSION

This multi-task deep learning approach effectively combines the benefits of both segmentation and classification techniques, resulting in improved accuracy and efficiency in identifying esophageal tumors on CT slices for radiotherapy planning.

HDAC-Mediated Glial Crosstalk Mediates Radiation Induced Memory Changes from Whole Brain Radiation in a Mouse Model

PURPOSE/OBJECTIVE(S)

Prior work demonstrated radiation sensitivity can be regulated via Class III HDAC-mediated intracellular DNA damage response coordinated with Wnt-beta catenin signaling. We hypothesized that radiation induced functional alterations in HDAC mediated glial crosstalk in the CNS produce intercellular signaling alterations leading to phenotypic changes in cognition following whole brain radiation exposure.

MATERIALS/METHODS

Primary human astrocytes, human astrocytoma (U251), and immortalized human microglia (HMC3) were examined in vitro in response to treatment with conditioned media isolated from irradiated glial cells. Prior to treatment with either single-dose or fractionated radiation schedules, cells were transfected with siRNA expression vector for Sirt2, a class III HDAC, versus scrambled controls. Quantitative PCR and immunoblots for neurotransmitters, metabolism, and inflammatory markers were obtained. Cells exposed to conditioned media were examined by immunofluorescence for cytoskeletal alterations and changes in junctional proteins. The findings were correlated with in vivo qPCR and immunohistochemical changes in brain tissue and functional memory changes in Sirt2 knockout versus wild type mice after whole brain radiation using novel object recognition testing at 2 weeks and 6 month post radiation timepoints. Statistical analysis was performed using paired Students T test between treated and control groups.

RESULTS

Cells treated with conditioned media produced from irradiated U251, astrocytes and microglia produced increased expression of inflammatory cytokines IL-6, IL-8, GM-CSF and VEGF. However, immunofluorescence of cells treated with conditioned media from irradiated Sirt2 knockdown microglia and primary astrocytes demonstrated qualitative disruptions in glutamate neurotransmitter metabolism and actin cytoskeletal alterations with changes in pseudopodia and lamellipodia after staining with phalloidin and neurofilament L, suggesting altered intercellular communication. Connexin 43 in gap junctions was increased >2-fold (p<0.05) after exposure to conditioned media, whereas E-cadherin in adherens junctions was not significantly affected. Novel object recognition testing of Sirt2 knockout mice demonstrated resistance to radiation induced memory decline from whole brain radiation at pre radiation day 5 versus post radiation days 5 and 185 compared to controls (p<0.05).

CONCLUSION

Glial crosstalk can be mediated via elimination of a Class III HDAC and appears to be a key mediator of radiation induced disruptions of intercellular communication in the CNS, connecting radiation to structural changes on the cell surface to synaptic activity and neurotransmitter metabolism, leading to functional disputations in recognition memory similar to what is experienced by patients receiving brain radiotherapy. These data suggest glial cross talk as a new therapeutic avenue to combat radiation induced cognitive dysfunction.

An Efficient Transformer Model for Synthesizing Dual Energy CT from Single Energy Scanner

PURPOSE/OBJECTIVE(S)

Dual-energy CT can be used to optimize radiation treatment. Recently, deep learning has been demonstrated to synthesize high-energy CT images from low-energy ones for dose reduction and lower CT system burden. As the state-of-the-art deep learning architecture, the computation burden of Transformer increases quadratically with the feature size, making the model training resource-demanding or even infeasible. Here, we introduce an efficient transformer for the balance between CT image synthesis quality and computational burden.

MATERIALS/METHODS

The model is a U-shape deep neural network with encoders and decoders built by Transformer blocks. The model input is low-energy 100kVp CT image and the output is high-energy 140kVp one. Each block has a Self Channel Correlation Unit (SCCU) and a Self Spatial Attention Unit (SSAU). Local shortcuts are applied for both units. Under-sampling operation achieved by pixel shuffling is used to obtain multi-scale feature maps, and the transformer block is applied on each feature scale. Symmetric skip connection sending features from shallow layers to deep layers, thus an additional 1 × 1 convolution is used for feature fusion in each decoder. In a SCCU, the feature is first mapped to one Query, one Key, and one Value. Then the Query and the Key tensors perform matrix multiplication to compute cross covariance of feature channels. The channel correlation score can be obtained by normalization of the covariance, and it is used to weight the Value tensor. As a result, the model complexity only increases linearly with the feature size. Besides the channel weighting, we enhance spatial information using SSAU, where the feature is mapped to two tensors. One tensor after activation is used to point-wisely calibrate another tensor. Additional Transformer blocks are cascaded to the last decoder for feature refinement. Because of the structure similarity of low- and high-energy CT images, a global shortcut is used to ease model training. Clinical iodine contrast-enhanced dual energy CT image datasets of 19 patients are used in this study. The dual-energy scanning is performed by a SOMATOM Definition Flash DECT scanner. We split the datasets into training dataset of 15 patients, validation dataset of 1 patient, and testing dataset of 3 patients. The image size is 512 × 512 with pixel size 0.5 × 0.5 mm2.

RESULTS

The U-Net model with 1.95M parameters and 44.87G FLOPS achieved the averaged PSNR value of 44.55 dB (s.t.d. 1.34) and averaged RMSE value of 0.0060 (s.t.d. 0.001). In comparison, our efficient Transformer with 1.408M parameters and 31.375G FLOPS achieved the averaged PSNR value of 44.78 dB (s.t.d. 1.37) and RMSE value of 0.0059 (s.t.d. 0.001), demonstrating our model has better performance with small model size and less computation.

CONCLUSION

The efficient Transformer model allows high-resolution CT image synthesis with small model scale and computation burden from low-energy CT image.

Deep Learning-Based Multi-Modality Segmentation of Primary Gross Tumor Volume in CT and MRI for Nasopharyngeal Carcinoma

PURPOSE/OBJECTIVE(S)

The delineation of primary gross tumor volume (GTV) of nasopharyngeal carcinoma (NPC) is an essential step for radiotherapy planning. In clinical practice, radiation oncologists manually delineate the GTV in planning CT with the help of diagnostic MRI. This is because NPC tumors are closely adjacent to many important anatomic structures, and CT and MRI provide complementary strength to accurately determine the tumor extension boundary. Manual delineation is time-consuming with the potential registration errors between MRI and CT decreasing the delineation accuracy. In this study, we propose a fully automated GTV segmentation method based on CT and MRI by first aligning MRI to CT, and then, segmenting the GTV using a multi-modality deep learning model.

MATERIALS/METHODS

We collected 104 nasopharyngeal carcinoma patients with both planning CT and diagnostic MRI scans (T1 & T2 phases). An experienced radiation oncologists manually delineated the GTV, which was further examined by another senior radiation oncologist. Then, a coarse to fine cross-modality registration from MRI to CT was conducted as follows: (1) A rigid transformation was performed on MRI to roughly align MRI to CT with similar anatomic position. (2) Then, the region of interest (RoI) on both CT and rigid-transformed MRI were cropped. (3) A leading cross-modality deformable registration algorithm, named DEEDS, was applied on the cropped MRI and CT RoIs to find an accurate local alignment. Next, using CT and registered MRI as the combined input, a multi-modality deep segmentation network based on nnUNet was trained to generate the GTV prediction. 20% patients were randomly selected as the unseen testing set to quantitatively evaluate the performance.

RESULTS

The quantitative NPC GTV segmentation performance is summarized in Table 1. The deep segmentation model using CT alone achieved reasonable high performance with 76.6% Dice score and 1.34mm average surface distance (ASD). When both CT and registered MRI were used, the segmentation model further improved the performance by 0.9% Dice score increase and 11% relative ASD error reduction, demonstrating the complementary strength of CT and MRI in determining NPC GTV. Notably, the achieved 77.5% Dice score and 1.19mm ASD by the multimodality model is among the top performing results reported in recent automatic NPC GTV segmentation using either CT or MRI modality.

CONCLUSION

We developed a fully automated multi-modal deep-learning model for NPC GTV segmentation. The developed model can segment the NPC GTV in high accuracy. With further optimization and validation, this automated model has potential to standardize the NPC GTV segmentation and significantly decrease the workload of radiation oncologists in clinical practice.

Development and Validation of a Deep Learning-Based Auto-Delineation of Target Volume and Organs at Risk in Pancreatic Cancer Radiotherapy

PURPOSE/OBJECTIVE(S)

The delineation of the clinical target volume (CTV), gross target volume (GTV) and organs at risk (OARs) is a crucial and laborious in pancreatic cancer radiotherapy. In this work, we propose and evaluate a three-dimensional (3D) novel convolutional neural network (CNN) for automatic and accurate CTV, GTV and OARs in pancreatic cancer.

MATERIALS/METHODS

A total of 120 computed tomography (CT) scans patients with pancreatic cancer were collected. A novel 3D CNN network, called ResUNet3D, was developed to achieve auto-delineation. 96 patients chosen randomly were used for training, 12 patients for validation, and 12 patients for testing. Meanwhile, the Dice similarity coefficient (DSC) and 95th percentile Hausdorff distance (HD95%) were used to assess the performance.

RESULTS

The DSC values for the test data were 80.9±8.6%, 77.5±5.6%, 94.5±1.3%, 66.2±13.4%, 73.6±7.6%, 79.0±8.7%, 94.1±1.9%, 94.6±1.4%, 87.3±5.8% for CTV, GTV, liver, duodenum, spinal cord, bowel, kidney left, kidney right, stomach. The corresponding HD95% values were 10.7±6.9mm, 7.8±5.7mm, 11.6±5.6mm, 18.6±5.6mm, 2.7±0.7mm, 17.7±8.6mm, 3.9±1.4mm, 3.7±1.9mm, 13.4±5.7mm, respectively. The average delineation time for one patient's CT images was within 5 seconds.

CONCLUSION

The experimental results demonstrate that the CTV, GTV and OARs delineated for pancreatic cancer by ResUNet3D achieved a close agreement with the ground truth. ResUNet3D could significantly reduce the radiation oncologists' contouring time.

Evaluation of 68Ga-Fibroblast Activation Protein Inhibitor vs. 18F-FDG as a Novel Radiotracer for Biologically Guided Radiation Therapy

PURPOSE/OBJECTIVE(S)

Real-time biology guided radiation therapy (BgRT) uses real-time positron emissions from a PET tracer during treatment to guide targeted radiation to cancerous lesions. Fibroblast activation protein alpha (FAP) is highly expressed on cancer-associated fibroblasts in tumors with low expression in normal tissues. While 18F-FDG-PET requires fasting and has background in the liver and brain, 68-Gallium labeled FAP inhibitor (FAPI) does not require fasting and has less background uptake. The goal of this study was to investigate the utility of FAPI as a potential universal fiducial for BgRT. We hypothesized that 68Ga-FAPI would be a better radiotracer than 18F-FDG, as assessed by the Normalized Minimal kBq/mL and the Normal Target Signal (NTS), two parameters used to gauge the suitability of BgRT.

MATERIALS/METHODS

PET-CTs were obtained for 50 patients with pancreatic, liver, lung, head & neck, and cervical cancer using 18F-FDG and 68Ga-FAPI (n = 10 for each). Four DICOM images were obtained per patient (FDG PET + CT, FAPI PET + CT). Radiation oncologists delineated the gross tumor volume (GTV) on PET images. A separate set of auto-contours were generated from the PET using an auto-threshold of 40% maximum SUV for all tumors. A 1 cm expansion was added to the GTV to create a ring around the physician-generated contours and auto-contours. The following parameters were measured: GTV volume, SUV max of GTV, SUV mean of GTV, Normalized Minimal kBq/mL within the GTV, and NTS (= SUV max/Ring SUV mean). Values were compared using paired t-test. For the BgRT product with similar calculations, the required Normalized Minimal kBq/mL is > 5 kBq/mL; the required NTS is > 2.7 for treatment planning and > 2.0 for BgRT delivery.

RESULTS

The Normalized Minimal kBq/mL for FAPI was > 5 kBq/mL for all tumors and greater for auto-contoured GTVs compared to physician-contoured GTVs. The mean NTS for the auto-contours for all tumor sites was > 2.0. In addition, there was a statistically significant increase in the NTS for FAPI compared to FDG in pancreatic, liver and head & neck cancers. In pancreatic cancer, there was a statistically significant increase in Normalized Minimal kBq/mL for FAPI compared to FDG (26.0 vs 14.2) (p = 0.01) and the SUVmax of FAPI was almost double that of FDG (15.9 vs 8.2) (p = 0.01). FAPI had no background in the liver, but had high background in the uterus, suggesting it may have a role in liver cancer but not cervical cancer.

CONCLUSION

This is the first study demonstrating the potential superiority of 68Ga-FAPI compared to 18F-FDG as a biologic fiducial for BgRT when treating pancreatic, liver and head & neck cancers, with a similar efficacy for lung cancer. Our results indicate that auto-contoured GTVs generate a higher NTS than physician-contoured GTVs but all are > 2.0. In addition, the Normalized Minimal kBq/mL for auto-contours is > 5 kBq/mL for all tumors. As hypothesized, FAPI-based BgRT is most likely to be successful when treating tumors with significant desmoplastic stroma, such as pancreatic cancer.

Comparing 90-Day Post-Operative Mortality after Neoadjuvant Proton-Based vs. Photon-Based Chemoradiotherapy for Esophageal Cancer

PURPOSE/OBJECTIVE(S)

Standard of treatment for locally advanced esophageal cancer consists of chemoradiotherapy (CRT) followed by surgery. Evidence suggests that proton beam therapy (PBT) results in lower toxicity and fewer post-operative complications compared to photon-based radiotherapy (RT). Mortality in the first 90 days after surgery is a rare event occurring in 2-8% of patients, with higher reported rates (of up to 17%) in older patients. This 90-day mortality (90DM) rate is an important measure of post-operative (non-oncologic) mortality as a proxy of quality of care. We hypothesize that PBT could reduce the incidence of 90DM compared to photon-based RT.

MATERIALS/METHODS

From a single-center retrospectively acquired database patients with esophageal cancer treated with neoadjuvant CRT and esophagectomy in 1998-2022 were selected. Univariable logistic regression analyses were used to study the associations of RT modality and other patient- and treatment-related characteristics with 90DM. Subsequently, 3 separate methods were applied to adjust for confounding bias. These included multivariable logistic regression, 1:1 nearest-neighbor propensity score matching (PSM), and inverse probability of treatment weighting (IPTW). Finally, stratified analyses for patient groups aged ≥67 vs. <67 years were performed.

RESULTS

A total of 894 eligible patients were included (PBT, n = 202; photon-based RT, n = 692). PBT patients had a significantly higher age, better performance score, and a higher number of comorbidities. The 90DM rate was 5 (2.5%) in the PBT group and 29 (4.2%) in the photon-based RT group (p = 0.262). Significant univariable predictors of 90DM included higher age and tumor location. After multivariable adjustment, PBT vs. photon therapy was not significantly associated with 90DM (OR 0.49, 95% CI 0.18-1.31). The 90DM rates in the PSM cohort (n = 181 vs. n = 181) were 2.8% for PBT and 3.3% for photon-based RT (p = 0.379). The 90DM rates in the IPTW cohort were 2.8% for PBT and 4.1% for photon-based RT (p = 0.427). In the full cohort, stratified analysis for age groups revealed that in patients aged ≥67 years, PBT was associated with a decreased risk of 90DM compared to photon-based RT (1.3% vs. 8.8%; p = 0.046), which was not the case in patients aged <67 years. In the PSM cohort, a comparable (but non-significant) difference was observed in favor of PBT in patients aged ≥67 years (i.e., 1.5% vs. 7.5%; p = 0.099). Within-group analyses in the original cohort demonstrated that a higher age significantly increased the risk of 90DM within the photon-based RT group (8.8% vs. 2.7% for age ≥67 vs. <67 years; p = 0.001), but not within the PBT group (1.3% vs. 3.2%; p = 0.398).

CONCLUSION

Post-operative 90DM after esophagectomy for cancer was not significantly different between PBT and photon-based neoadjuvant CRT. However, among older patients we observed a signal that PBT may reduce the risk of 90DM. Higher age increased the risk of 90DM in patients who underwent photon-based RT, but not in patients who underwent PBT.

The Incidence and Prognosis Value of Perineural Invasion in Rectal Carcinoma: From Meta-Analyses and Real-World Clinical Pathological Features

AIMS

Perineural invasion (PNI) is a special type of metastasis of several cancers and has been reported as being a factor for poor prognosis in colorectal carcinoma. However, investigations of PNI in only rectal cancer and a comprehensive analysis combining meta-analyses with real-world case studies remain lacking.

MATERIALS AND METHODS

First, articles from 2000 to 2020 concerning the relationship between PNI and rectal cancer prognoses and clinical features were meta-analysed. Subsequently, we carried out a retrospective analysis of 312 rectal cancer cases that underwent radical surgery in the real world. The incidence of PNI and the relationship between PNI and prognosis, as well as clinicopathological factors, were investigated.

RESULTS

The incidence of PNI was 23.09% and 33.01% in the meta-analysis and clinical cases, respectively. PNI occurred as early as stage I (2.94%). Moreover, neoadjuvant therapy significantly reduced the PNI-positive rate (20.34% versus 26.54%). Both meta-analysis and real-world clinical case studies suggested that PNI-positive patients had poorer prognoses than PNI-negative patients. We established an effective risk model consisting of T stage, differentiation and lymphovascular invasion to predict PNI in rectal cancer.

CONCLUSION

PNI is a poor prognostic factor for rectal cancer and could occur even in stage I. Additionally, neoadjuvant therapy could sufficiently reduce the PNI-positive rate. T stage, lymphovascular invasion and differentiation grade were independent risk factors for PNI and the risk model that included these factors could predict the probability of PNI.

A prospective multicentre controlled study of Gaoweikang (Chinese multiherb extract-based tincture) used in high-risk HPV infections

OBJECTIVE

The aim of the study was to investigate the safety and antiviral efficacy of a Chinese multiherb extract-based tincture (GWK) on a population of patients with high-risk human papilloma (hrHPV) infections and hrHPV-caused cervical low-grade squamous intraepithelial lesions (LSILs).

PATIENTS AND METHODS

Patients with persistent hrHPV infection were enrolled in Group A, including A1 subjects, who received the intervention, and A2 subjects, who received the control. Patients with hrHPV infection causing cervical LSIL were enrolled in Group B, which included B1 subjects, who received the intervention, and B2 subjects, who served as the control. For Groups A1 and B1, hrHPV was tested at 3 months (M3) and 6 months (M6) after the intervention. The side effects were also analyzed.

RESULTS

At baseline (D0), a total of 99 patients were enrolled in Group A, with 50 subjects in Group A1 and 49 subjects in Group A2. A total of 91 patients were enrolled in Group B, with 45 subjects in Group B1 and 46 subjects in Group B2. There was no significant difference in the characteristics, including average age, age stratification, and HPV genotype. At M6, both Group A1 and Group B1 had a higher hrHPV clearance rate than the control group (A1/A2: 80.0% vs. 20.4%; B1/B2: 64.4% vs. 15.2%, p<0.001). At M6, the effective rates of Group A1 and Group B1 were 84% (42/50) and 68.9% (31/45), respectively. The side effect rates of Groups A1 and B1 were 11.5% (6/52) and 11.1% (5/45), respectively. Most adverse reactions involved local discomfort, including vulvar erythema, vulvar itch, increased vaginal discharge, cervical bleeding, and mild pain in the lower abdomen. Univariate logistic regression analysis showed that the intervention had an OR of 12 (95% CI 4.431-32.50) for clearing persistent HPV infection (p<0.001). For cervical LSIL, the intervention had an OR of 10.1 for clearing persistent HPV infection (95% CI 3.68-27.7) (p<0.001).

CONCLUSIONS

The results of this study suggest that the Chinese multiherb extract-based tincture GWK is safe and well tolerated. Furthermore, this preliminary study showed that this Chinese multiherb extract-based tincture is helpful for promoting HPV clearance in cases of persistent HPV and HPV-induced LSIL.

Improvement of soil acidification and ammonium nitrogen content in tea plantations by long-term use of organic fertilizer

Soil acidification is common in some Chinese tea plantations, which seriously affected growth of tea trees. Hence, it is essential to explore soil remediation in acidified tea plantations for sustainable development of the tea industry. We sought to determine how different fertilizers affect acidified soil and their N transformation in tea plantations. Different fertilizers were used on acidified tea plantation soils for 4 years (2017-2021), and changes in soil pH, indices related to soil N transformation and tea yield were analysed to construct interaction networks of these indices and find which had the largest influence on fertilization. Long-term use of sheep manure reduced soil acidification, increased soil pH, enhanced the number and intensity of N-fixing and ammonifying bacteria, urease, protease, asparaginase and N-acetamide glucose ribosidase activity and nifH gene expression. This treatment reduced the number and intensity of soil nitrifying and denitrifying bacteria, nitrate reductase and nitrite reductase activity, while the expression of amoA-AOA, nirK, nirS, narG and nosZ in turn increased ammonium N content of the soil, reduced nitrate N content, and enhanced tea yield. Topsis index weight analysis showed that ammonium N content in the soil had the largest impact among fertilization effects. Long-term use of sheep manure was beneficial in restoring the balance of the micro-ecosystem in acidified soil. This study provides an important practical basis for soil remediation and fertilizer management in acidified tea plantation soils.

Ceruloplasmin regulating fibrosis in orbital fibroblasts provides a novel therapeutic target for Graves' orbitopathy

PURPOSE

In diagnosing the pathogenesis of Graves' orbitopathy (GO), there is a growing interest in fibrosis generated by orbital fibroblasts (OFs); nevertheless, the involvement of ceruloplasmin (CP) in OFs remains unknown.

METHODS

Differentially expressed genes (DEGs) were identified through bioinformatic analysis. OFs were isolated from orbital tissue and identified with immunofluorescent staining. The levels of DEGs were validated in GO tissue samples and TGF-β-challenged OFs, and CP was selected for the following laboratory investigations. CP overexpression or knockdown was achieved, and cell viability and fibrosis-associated proteins were investigated to assess the cell phenotype and function. Signaling pathways were subsequently investigated to explore the mechanism of CP function in OFs.

RESULTS

CP and cathepsin C (CTSC) are two overlapped DEGs in GSE58331 and GSE105149. OFs were isolated and identified through fibrotic biomarkers. CP and CTSC were downregulated in GO tissue samples and TGF-β-challenged OFs. CP overexpression or knockdown was achieved in OFs by transducing a CP overexpression vector or small interfering RNA against CP (si1-CP or si2-CP) and verified using a qRT-PCR. CP overexpression inhibited cell viability and reduced the levels of α-SMA, vimentin, fibronectin, and collagen I, whereas CP knockdown exerted opposite effects on OFs. CP overexpression inhibited the phosphorylation of Smad3, Erk1/2, p38, JNK, and AKT; conversely, CP knockdown exerted opposite effects on the phosphorylation of factors mentioned above.

CONCLUSION

CP was downregulated in GO and suppressed the expression of fibrosis-associated proteins in both GO and normal OFs. CP might serve as a promising therapeutic agent in the treatment regimens for GO.

Long-Term Follow-Up Analysis of NRG Oncology RTOG 0415: A Randomized Phase III Non-Inferiority Study Comparing Two Fractionation Schedules in Patients with Favorable-Risk Prostate Cancer

PURPOSE/OBJECTIVE(S)

To assess whether the efficacy of a hypofractionated (H) schedule is no worse than a conventional (C) schedule in men with low-risk prostate cancer.

MATERIALS/METHODS

Accrual began April 2006 and ended in December 2009. 1115 men with favorable-risk prostate cancer were randomly assigned 1:1 to a conventional (C) schedule (73.8 Gy in 41 fractions over 8.2 weeks) or to a hypofractionated (H) schedule (70 Gy in 28 fractions over 5.6 weeks). The trial was designed to establish with 90% power and alpha = 0.05 that (H) results in 5-year disease-free survival (DFS) that is not lower than (C) by more than 7% (hazard ratio (HR) < 1.52). Protocol specified secondary endpoints evaluated for noninferiority include: biochemical recurrence (BR), local progression, disease-specific survival, and overall survival.

RESULTS

One thousand ninety-two protocol eligible men were analyzed: 542 to C and 550 to H. Median follow-up is 12.75 years. Baseline characteristics were not different according to treatment arm. The estimated 12-year DFS is 56.1% (95% CI 51.5, 60.5) in the C arm and 61.8% (57.2, 66.0) in the H arm. The DFS hazard ratio (H/C) is 0.85 (0.71-1.03), confirming non-inferiority (p<0.001). Twelve-year cumulative incidence of biochemical recurrence (BR) was 17.0% (CI 13.8, 20.5) in the C-RT and 9.9% (CI 7.5, 12.6) in the H-RT arm; (HR = 0.56, (0.40-0.78) suggesting improved efficacy with H. Additional pre-specified secondary endpoints were non-inferior Late Grade ≥ 3 GI toxicity is 3.2% (C) vs. 4.4% (H), Relative risk (RR) for H vs. C 1.39 (CI 0.75, 2.55) Late Grade ≥ 3 GU toxicity is 3.4% (C) vs. 4.2% (H), RR = 1.26 (CI 0.69, 2.30).

CONCLUSION

In men with favorable-risk prostate cancer, long-term disease-free survival is non-inferior with 70 Gy in 28 fractions compared to 73.8 Gy in 41 fractions. The risk of BR is reduced with moderate hypofractionation. No differences in late Grade ≥3 GI/GU toxicity were observed between the arms. (ClinicalTrials.gov identifier: NCT00331773).

2V-CBCT: Two-Orthogonal-Projection Based CBCT Reconstruction and Dose Calculation from Real CBCT Projection Data

PURPOSE/OBJECTIVE(S)

Not all radiation therapy (RT) treatments/fractions have CBCT acquired, but two orthogonal projections (i.e., KV radiography) are always available. This work demonstrates the feasibility of two-orthogonal-projection-based CBCT (2V-CBCT) reconstruction and dose calculation for RT from real CBCT projection data, which is the first 2V-CBCT feasibility study using real projection data, to the best of our knowledge.

MATERIALS/METHODS

2V-CBCT is a severely ill-posed inverse problem for which we propose a coarse-to-fine learning strategy. First, a 3D deep neural network that can extract and exploit the inter-slice and intra-slice information is adopted to predict the initial 3D volumes. Then, a 2D deep neural network is utilized to fine-tune the initial 3D volumes slice-by-slice. During the fine-tuning stage, a perceptual loss based on multi-frequency features is employed to enhance the image reconstruction. Dose calculation results from both photon and proton RT demonstrate that 2V-CBCT provides comparable accuracy with full-view CBCT based on real projection data.

RESULTS

The proposed method was evaluated on real HN data acquired from on-board CBCT scanners rather than the low-resolution simulated data or down-sampled data. Both visual assessment and quantitative analysis demonstrate that the proposed coarse-to-fine learning strategy has the potential to produce satisfactory volumetric images from two orthogonal projections. Furthermore, we assessed the utility of 2V-CBCT in RT. The results show that the dose distribution maps, dose-volume histograms, and dose parameters calculated using 2V-CBCT have comparable accuracy with the counterparts calculated using the corresponding full-view CBCT for both photon and proton RT. In the table, the methods under comparison are pCT (planning CT), FV-CBCT (CBCT reconstructed with full-view projection data), and 2V-CBCT (CBCT reconstructed with two orthogonal projections).

CONCLUSION

A new effective 2V-CBCT reconstruction method is proposed and validated using real CBCT projection data, which can potentially provide comparable dose calculation accuracy for both photon and proton RT.

First Demonstration of the Commissioning of a New Multi-Modality Radiotherapy Platform

PURPOSE/OBJECTIVE(S)

A new multi-modality radiotherapy platform was developed and introduced into clinical application, which has received US FDA 510k(K210921) and National Medical Products Administration (NMPA) clearance in China (20223050973). This study, for the first time, presents the technological characteristics and commissioning results of the new platform.

MATERIALS/METHODS

The platform consists of 3 modules: linear accelerator, rotating gamma system, and a kV imaging system within an O-ring gantry. The O-ring gantry can rotate continuously achieved by using a slip ring. The Linac delivers a 6 MV FFF photon beam with a variable dose rate of 50 to 1400 MU/min. The delivery techniques include 3D-CRT, IMRT, and VMAT. The rotating gamma system utilizes 18 Co-60 sources with a reference dose rate of 350 cGy/min. The image-guided techniques consist of kV-kV pairs and kV-CBCT. The X-ray intensity-modulated radiotherapy and γ-ray stereotactic radiotherapy can be delivered on the same platform. The acceptance test and commissioning were performed following the vendor's customer acceptance tests (CAT) and several AAPM Task Group reports/guidelines. Regarding the Linac, all applicable validation tests recommended by the MPPG 5.a (basic photon beam model validation, IMRT/VMAT validation, E2E tests, and patient-specific QA) were performed. For the rotating gamma system, the absorbed doses were measured using a PTW31014 and PTW60016. EBT3 films were employed to measure the relative output factors (ROFs). The E2E tests were performed using a PTW31014 and EBT3 films. The coincidence between the imaging isocenter and the Linac/gamma treatment isocenter was investigated using EBT3 films. The image quality was evaluated regarding the contrast-to-noise ratio (CNR), spatial resolution, and uniformity.

RESULTS

All tests included in the CAT met the vendor's specifications. All MPPG 5.a tests complied with the tolerances. The confidence limits for IMRT/VMAT validation were achieved according to TG-119. The point dose differences were below 1.68% and gamma pass rates (3%/2 mm) were above 95.9% for the Linac E2E tests. All plans of patient-specific QA had point dose differences below 1.79% and gamma pass rates (3%/2 mm) above 96.1% suggested by TG-218. For the rotating gamma system, the differences between the calculated and measured absorbed doses were below 1.86%. The ROFs calculated by the TPS were independently confirmed within 2% using EBT3 films. The point dose differences were below 2.57% and gamma pass rates (2%/1 mm) were above 95.3% for the E2E tests. The coincidence between the imaging isocenter and the Linac/gamma treatment isocenter was within 0.5 mm. The image quality fully complied with the vendor's specifications regarding the CNR, spatial resolution, and uniformity.

CONCLUSION

This is the first report about the commissioning of a new multi-modality radiotherapy platform. The platform has been successfully commissioned and exhibits good performance in mechanical and dosimetry accuracy.

Measurement-induced entanglement and teleportation on a noisy quantum processor

Measurement has a special role in quantum theory1: by collapsing the wavefunction, it can enable phenomena such as teleportation2 and thereby alter the 'arrow of time' that constrains unitary evolution. When integrated in many-body dynamics, measurements can lead to emergent patterns of quantum information in space-time3-10 that go beyond the established paradigms for characterizing phases, either in or out of equilibrium11-13. For present-day noisy intermediate-scale quantum (NISQ) processors14, the experimental realization of such physics can be problematic because of hardware limitations and the stochastic nature of quantum measurement. Here we address these experimental challenges and study measurement-induced quantum information phases on up to 70 superconducting qubits. By leveraging the interchangeability of space and time, we use a duality mapping9,15-17 to avoid mid-circuit measurement and access different manifestations of the underlying phases, from entanglement scaling3,4 to measurement-induced teleportation18. We obtain finite-sized signatures of a phase transition with a decoding protocol that correlates the experimental measurement with classical simulation data. The phases display remarkably different sensitivity to noise, and we use this disparity to turn an inherent hardware limitation into a useful diagnostic. Our work demonstrates an approach to realizing measurement-induced physics at scales that are at the limits of current NISQ processors.

Safety and Efficacy of Hypofractionated Radiotherapy Combined with Tyrosine Kinase Inhibitors in Patients with Lung Metastases after Liver Transplantation for Hepatocellular Carcinoma

PURPOSE/OBJECTIVE(S)

We evaluated the safety and efficacy of hypofractionated radiotherapy (HFRT) combined with tyrosine kinase inhibitors (TKIs) in patients with pulmonary metastases after orthotopic liver transplantation (OLT) for hepatocellular carcinoma (HCC).

MATERIALS/METHODS

Twenty-five patients with lung metastases after OLT for HCC who underwent HFRT using helical tomotherapy concomitantly with TKIs (sorafenib or lenvatinib) were retrospectively. The primary endpoint was progression-free survival (PFS). The secondary endpoints were overall survival (OS), local control rate (LCR), objective response rate (ORR), and treatment-related side effects.

RESULTS

The median follow-up time was 35.5 months, with a median interval from OLT to lung metastasis of 15.3 months. The median PFS and OS were 9.9 and 32.7 months, respectively. The 1-, 2-, and 3-year PFS and OS rates were 36.0%, 16.0%, and 12.0%, and 84.0%, 52.0%, and 20.0%, respectively. The LCR of pulmonary metastases at 1 year was 100%, whereas the two-year LCR was 76.9%. The 1- and 2- year ORRs were 95.2% and 69.2%, respectively, with no grade > 2 adverse events. Radiation pneumonitis was observed in 17 patients (68.0%). Grade 1 pneumonitis occurred in 15 patients (60.0%), and grade 2 pneumonitis occurred in 2 patients (8.0%).

CONCLUSION

The combination therapy of HFRT with TKIs is a feasible, safe, and promising approach in the treatment of pulmonary metastases for HCC after OLT.

Patient-Adaptive Automated Segmentation in Daily kVCT Images for Radiotherapy of Head and Neck and Prostate Cancer

PURPOSE/OBJECTIVE(S)

The purpose of this study was to examine the use of transfer learning in deep learning-based auto-segmentation of daily kilovoltage computed tomography (kVCT) images for patient-specific adaptive radiotherapy. Using data from the first cohort of patients treated with the innovative BgRT system, the objective of this study was to evaluate the potential benefits of this approach in facilitating efficient and effective adaptive radiotherapy.

MATERIALS/METHODS

For the head and neck (HaN) site and pelvic site, we first trained a deep convolutional segmentation network using a population dataset, consisting of 67 and 56 patient cases, respectively. This population network was then fine-tuned for a specific patient using a transfer learning approach, adapting the network weights. The auto-segmentation network utilized in this study was a 23-layer U-Net with batch normalization, a dropout rate of 0.5, and four skip connections between the encoder and decoder at different levels. We used initial planning CT and 5-26 sets of daily kVCT scans with a total of 8,039 images for patient-specific learning in the 6 HaN cases and 4 pelvic cases, particularly analyzing the relationship between the number of sequential patient-specific training data and the performance of the auto-segmentation. We compared the performance of the patient-specific network with the population network and the clinical rigid registration method, using the Dice similarity coefficient (DSC) as the evaluation metric. Additionally, we investigated the corresponding dosimetric impacts of the different auto-segmentation and registration methods.

RESULTS

The patient-specific network showed improved mean DSC scores of 0.88 and 0.90 for three HaN organs at risk (OARs) and eight pelvic targets and OARs, respectively, compared to the population network (0.70 and 0.63) and the registration method (0.72 and 0.72). The DSC of the patient-specific network steadily improved as the number of longitudinal training cases increased, reaching near saturation after 6 training cases. The use of the patient-specific auto-segmentation resulted in a reduction of the mean discrepancy in target and OAR doses between delivery and planning from 5.5% with the clinical rigid registration to 1.1%.

CONCLUSION

The use of patient-specific transfer learning in auto-segmenting kVCT images showed higher accuracy compared to a conventional population network and clinical registration-based method. This approach holds promise for enhancing dose evaluation accuracy in adaptive radiotherapy.

Homeostatic Balance of Gut Microbiota in Head and Neck Squamous Cell Carcinoma Patients during Radiotherapy

PURPOSE/OBJECTIVE(S)

Radiotherapy is the major treatment for head and neck squamous cell carcinoma (HNSCC). Oral microbiota changes have been described before. However, gut microbiota changes in HNSCC patients who received local radiotherapy remain unclear. We aim to investigate the dynamic change of gut microbiota composition in HNSCC patients undergoing radiotherapy and to construct the radiotherapy related gut microbiota database in HNSCC patients.

MATERIALS/METHODS

We enrolled 47 HNSCC patients who scheduled with radiotherapy solely. Intensity-modulated radiotherapy (IMRT) was the standard radiotherapy technique for all the enrolled patients. The field was irradiated with a total dose of 60-66Gy in 30-33 fractions. Fecal pellets were collected at three time points. Bacterial genomic DNA was isolated using magnetic beads and then analyzed by the Illumina MiSeq Sequencing System based on the V3-V4 hypervariable regions of the 16S rRNA gene.

RESULTS

A total of 194 genera which belonged to 27 phyla were found in 141 samples. Increased abundance of microbiota in diversity and richness was observed in mid-radiotherapy group. Moreover, Bacteroides, Blautia, and Phascolarctobacterium were three main genera in all three groups and the mid-radiotherapy group had the highest relative abundance of Phascolarctobacterium. What's more, most significantly altered bacteria shared the same variation pattern which was increased in mid-radiotherapy while decreased to the almost same level of as pre-radiotherapy in post-radiotherapy group.

CONCLUSION

Local radiotherapy can affect the composition of the gut microbiota in HNSCC patients during the mid-term of radiotherapy. However, self-stabilized ability maintained the gut microbiota homeostasis in the end.

A Comparison of Two Plan Optimization Methods in Three-Dimensional Brachytherapy for Cervical Cancer

PURPOSE/OBJECTIVE(S)

To compare dose distributions created by using two Inverse Planning Simulated Annealing (IPSA) and Hybrid Inverse Planning Optimization (HIPO) in three-dimensional (with CT image guidance) brachytherapy planning for cervical cancer.

MATERIALS/METHODS

Brachytherapy plans for thirty patients with cervical cancer were created using the IPSA and HIPO algorithms (The IPSA algorithm is calculated based on the anatomical structure, and the simulated annealing algorithm is used to optimize the residence time, and the HIPO algorithm is the optimization and replacement for the IPSA). To obtain a HIPO plan, a manually optimized post-loading treatment plan was applied to these 30 patients, and then the treatment plan was reoptimized using the HIPO algorithm based on the original image information. Individual patients will consider interpolation therapy according to the needs of their condition. The types of plans were compared based on a variety of dose volume parameters, including the mean dose covering 90% of high-risk clinical target volume (D90 for HR-CTV), the mean dose to 2 cm3 volume (D2cc) for bladder, rectum, intestine and sigmoid, and average treatment time were compared and analyzed.

RESULTS

Compared with the two groups of plans, mean value of HR-CTV D90 for the HIPO plans was (585 cGy), which was significantly higher than that for the IPSA plans (567 cGy. This difference is statistically significant (P<0.05). The HIPO plans had mean D2cc 422±47 cGy for bladder, 403±38 cGy for rectum, which were lower than those from the SA plans, i.e., 446±42 cGy for bladder and 427±31 cGy for rectum; These differences were statistically significant (t = 5.125, 4.729, P <0.05). There was no statistically significant difference in the sigmoid D2cc doses between the two algorithms. The treatment times for delivering the two types of plans were not significant different.

CONCLUSION

Depending on patient's condition, whether conventional brachytherapy therapy or interpolation therapy is used, the use of the HIPO algorithm to design the treatment regimen without additional treatment time can provide a higher target dose than the manually optimized brachytherapy regimen. Meanwhile, the bladder and rectum doses can be reduced to a certain extent under the premise of ensuring that the target dose met the treatment requirements. There is some increasement for the intestine dose with HIPO planning group, but the dose limits required by the guidelines are still met clinical requirement.

Early disease intervention with guselkumab in psoriasis leads to a higher rate of stable complete skin clearance ('clinical super response'): Week 28 results from the ongoing phase IIIb randomized, double-blind, parallel-group, GUIDE study

BACKGROUND

Guselkumab is an interleukin (IL)-23 inhibitor with demonstrated efficacy in patients with psoriasis.

OBJECTIVES

Evaluate the impact of early disease intervention on clinical responses following 28 weeks of guselkumab treatment in patients with moderate-to-severe plaque psoriasis. Correlate clinical response and disease duration data with serum biomarker data.

METHODS

GUIDE is a phase IIIb randomized, double-blind, parallel-group, multicentre study of adults with moderate-to-severe plaque psoriasis. In study part 1, patients with a short disease duration (SDD [≤2 years]) or a long disease duration (LDD [>2 years]) received guselkumab 100 mg at Week (W) 0, 4, 12, and 20. Those achieving complete skin clearance at W20 and W28 were defined as a super responder (SRe). A multivariable logistic regression analysed the association between baseline factors and the likelihood of becoming an SRe. The relationship between clinical response, disease duration and serum biomarker data was assessed at W0 and 4.

RESULTS

In total, 880 patients were enrolled (SDD/LDD = 40.6%/59.4% of patients). More SDD than LDD patients achieved absolute Psoriasis Area and Severity Index (PASI) = 0 at W28 (51.8% vs. 39.4%) and were SRes (43.7% vs. 28.1% [overall 34.4%]). SDD patients also achieved PASI = 0 quicker than LDD patients (median 141 vs. 200 days). Disease duration and prior biologic use had the greatest impact on becoming an SRe, with no strong association among these independent variables. At baseline, there were no significant differences in the serum biomarker levels of IL-17A, IL-17F, IL-22 and β-defensin 2 between SDD and LDD patients, or between SRe and non-SRe patients. Guselkumab rapidly decreased these markers of systemic inflammation across all patient groups analysed at W4. Guselkumab was well tolerated.

CONCLUSIONS

Guselkumab efficacy was consistent across subpopulations, on the skin and systemically. The proportion of SRes was higher in SDD than LDD patients, indicating early treatment intervention may improve clinical outcomes.

Modelling enzyme inhibition toxicity of ionic liquid from molecular structure via convolutional neural network model

Deep learning (DL) methods further promote the development of quantitative structure-activity/property relationship (QSAR/QSPR) models by dealing with complex relationships between data. An acetylcholinesterase inhibitory toxicity model of ionic liquids (ILs) was established using a convolution neural network (CNN) combined with support vector machine (SVM), random forest (RF) and multilayer perceptron (MLP). A CNN model was proposed for feature self-learning and extraction of ILs. By comparing with the model results through feature engineering (FE), the model regression results based on the CNN model for feature extraction have been substantially improved. The results showed that all six models (FE-SVM, FE-RF, FE-MLP, CNN-SVM, CNN-RF, and CNN-MLP) had good prediction accuracy, but the results based on the CNN model were better. The hyperparameters of six models were optimized by grid search and the 10-fold cross validation. Compared with the existing models in the literature, the model performance has been further improved. The model could be used as an intelligent tool to guide the design or screening of low-toxicity ILs.

Prospective Clinical Adoption of Artificial Intelligence for Organ Contouring in Head and Neck Radiation Treatment Planning

PURPOSE/OBJECTIVE(S)

Patients that undergo head and neck (H&N) radiation therapy (RT) require laborious delineation of organs-at-risk (OARs) on computed tomography (CT) scans in a treatment planning system (TPS) to minimize radiation to normal tissue. This task can be completed rapidly and accurately with recently developed artificial intelligence-based semantic segmentation models. The current study aims to deploy and evaluate a strategy for improving clinical practice with this technology.

MATERIALS/METHODS

Deep learning models were trained and tested with CT scans and OAR contours from previous H&N RT cases at our clinic. Two medical physicists vetted the models and selected a 2.5D U-Net for further implementation. The model was embedded in a dedicated server at the hospital, programmed to read H&N CT scans staged for import into the TPS, generate auto-contours, and write them into a TPS-compatible format made available alongside the scan. In the pilot implementation, the auto-contouring service was utilized for more than 60 cases, prospectively. The auto-contours were quantitatively evaluated against the treatment-approved contours to determine how much modification was performed by the clinical team.

RESULTS

The 2.5D U-Net selected for clinical integration segments 21 OARs in less than 3 minutes per scan. Across all the prospective cases, the mean Dice score and mean 95th percentile Hausdorff distance (mm) between the auto-contour and treatment-approved contour for each of the 21 OARs were as follows, respectively: brainstem (0.93, 1.94), optic chiasm (0.70, 2.96), left cochlea (0.69, 2.37), right cochlea (0.68, 2.44), esophagus (0.88, 2.46), left globe (0.93, 1.50), right globe (0.93, 1.63), glottis (0.91, 2.13), larynx (0.93, 2.76), mandible (0.90, 4.86), left optic nerve (0.78, 1.64), right optic nerve (0.82, 1.65), oral cavity (0.86, 8.46), left parotid gland (0.91, 2.78), right parotid gland (0.91, 2.39), pharynx (0.85, 2.39), spinal cord (0.87, 2.27), left submandibular gland (0.85, 3.46), right submandibular gland (0.83, 3.69), left temporal lobe (0.94, 2.20), and right temporal lobe (0.95, 2.09). The auto-contours for the optic chiasm, optic nerves, cochleas, and submandibular glands differed substantially from the final contours, a finding corroborated by the clinical team; the rest were clinically acceptable with minor or no edits necessary.

CONCLUSION

The proposed strategy provides a sophisticated starting point for treatment planning that has garnered overall favorable feedback from the participating radiation oncologists and dosimetrists. Consequently, the technique is being extended to other treatment sites.

Stereotactic Body Radiotherapy Combined with Sintilimab in Patients with Recurrent or Oligometastatic Hepatocellular Carcinoma: A Phase II Clinical Trial

PURPOSE/OBJECTIVE(S)

The anti-tumor activity and tolerability of stereotactic body radiotherapy (SBRT) and PD-1 inhibitors have been illustrated in retrospective studies, but the results vary across a broad range. This study aimed to assess the clinical efficacy of SBRT combined with sintilimab in patients with recurrent or oligometastatic hepatocellular carcinoma (HCC).

MATERIALS/METHODS

This trial involved patients with recurrent or oligometastatic HCC intravenously treated with SBRT plus sintilimab every 3 weeks for 12 months or until disease progression. The primary endpoint was progression-free survival (PFS).

RESULTS

Twenty-five patients were enrolled from August 14, 2019, to August 23, 2021. The median treatment duration was 10.2 months. SBRT was delivered at a median dose of 54 in six fractions. The median follow-up time was 21.9 months, and 32 targeted lesions among 25 patients were evaluated for treatment response according to the Response Evaluation Criteria in Solid Tumors version 1.1. The median PFS was 19.7 months, with PFS rates of 68% and 45.3% at 12 and 24 months, respectively. The median overall survival (OS) was not reached, with OS rates of 91.5% and 83.2% at 12 and 24 months, respectively. The 1- and 2-year local control rate were 100% and 90.9%, respectively. The confirmed objective response rate and disease control rate was 96%, and 96%, respectively. Most adverse events were graded as 1 or 2, and grade 3 adverse events were observed in three patients.

CONCLUSION

SBRT plus sintilimab is an effective, well-tolerated treatment regimen for patients with recurrent or oligometastatic HCC.

The Robotic System for the Treatment of Locally Advanced Cervical Cancer with Stereotactic Body Radiotherapy Boost: Results of a Phantom-Based and Preliminary Study

PURPOSE/OBJECTIVE(S)

To fix uterocervical position, compensate uterocervical intrafraction motion, and thus improve the accuracy of dose delivery based on the robotic system for the treatment of locally advanced cervical cancer with stereotactic body radiotherapy boost.

MATERIALS/METHODS

CT images were acquired after robot arm implanted a fixator with fiducial markers into the cervix of pelvic phantom. The treatment plans were designed by contoured a simulated tumor lesion site. The fiducial markers position was obtained by real-time image guidance system and was registered with digitally reconstructed radiographs to calculate correlation error of six directions. The correlation error was delivered to the robotic arm to precisely adjust the position and posture of the fixator, and thus compensated uterocervical intrafraction movement through the interactive interface of the robotic system. The pressure sensor at the head of the fixator provided real-time feedback on the pressure value at the contact surface between the fixer and the cervix. The correlation error of six directions and the pressure value were extracted and analyzed from the log file.

RESULTS

The data from the log file indicated that the three translational direction correlation error of x, y and z were 0.19mm, 0.20mm and 0.10mm, respectively. The three rotational direction correlation error of roll, pitch and yaw were 0.25°, 0.21° and 0.23°, respectively. With the increase of the relative distance between cervix and pressure sensor, the mean value of pressure variation decreases gradually. When the relative distance is 0.5mm and 3mm, the mean value of pressure variation is approximately 76% and 32%, respectively.

CONCLUSION

The correlation accuracy of the robotic system meets the clinical requirements. The robot arm can fix and monitor the cervical motion in real time during radiotherapy. The robot system adjusts the position of the fixator to correct the uterocervical intrafraction motion error, which is feasible and has good clinical application prospect.

Anisotropic magnetoresistance and electronic features of the candidate topological compound praseodymium monobismuthide

PrBi, a sister member of the rare-earth monopnictide family, is an excellent candidate for studying extreme magnetoresistance and nontrivial topological electronic states. In this study, we perform angular magnetoresistance measurements as well as bulk and surface band structure calculations on this compound. PrBi's magnetoresistance is revealed to be significantly angle-dependent and shows a fourfold symmetry as always observed in the nonmagnetic isostructural counterparts, including LaSb, LaBi, and LuBi. Its angular magnetoresistance can be reproduced well using the semiclassical two-band model. The deduced parameters suggest that PrBi hosts an elongated electron pocket with a mobility anisotropy of ∼3.13 and is slightly uncompensated in its carrier concentration. Our bulk and surface band structure calculations confirm the anisotropic electronic features. Moreover, we reveal that a nodal-line-shaped surface state appears at the X̄ point, and is associated with the quadratic dispersion along the -X̄ direction, and the linear type-I Dirac dispersion along the X̄-M̄ direction. Owing to the type-I Dirac dispersion feature, PrBi could serve as a promising material platform for studying many unexpected physical properties, such as the highly anisotropic transport and valley polarization of electrons.

Multi-breed host rumen epithelium transcriptome and microbiome associations and their relationship with beef cattle feed efficiency

Understanding host-microbial interactions in the rumen and its influence on desirable production traits may lead to potential microbiota manipulation or genetic selection for improved cattle feed efficiency. This study investigated the host transcriptome and its correlation with the rumen archaea and bacteria differential abundance of two pure beef cattle breeds (Angus and Charolais) and one composite beef hybrid (Kinsella) divergent for residual feed intake (RFI; low-RFI vs. high-RFI). Using RNA-Sequencing of rumen tissue and 16S rRNA gene amplicon sequencing, differentially expressed genes (FDR ≤ 0.05, |log2(Fold-change) >|2) and differentially abundant (p-value < 0.05) archaea and bacteria amplicon sequence variants (ASV) were determined. Significant correlations between gene expression and ASVs (p-value < 0.05) were determine using Spearman correlation. Interesting associations with muscle contraction and the modulation of the immune system were observed for the genes correlated with bacterial ASVs. Potential functional candidate genes for feed efficiency status were identified for Angus (CCL17, CCR3, and CXCL10), Charolais (KCNK9, GGT1 and IL6), and Kinsella breed (ESR2). The results obtained here provide more insights regarding the applicability of target host and rumen microbial traits for the selection and breeding of more feed efficient beef cattle.

Systematic review with meta-analysis: effects of probiotic fungi on irritable bowel syndrome

Treatment of irritable bowel syndrome (IBS) remains challenging for clinicians. Probiotic fungi may act as candidate options for IBS treatment, but systematic evaluation of their clinical value remains scarce. This study is aimed to assess the efficacy and the safety of probiotic fungi for IBS treatment by means of systematic review and meta-analysis. PubMed, Embase, Web of Science, and the Cochrane Library, were searched up to June 2022. Randomised controlled trials recruited subjects with prescriptions of probiotic fungi were eligible. Efficacy and safety of probiotic fungi were re-evaluated. Continuous data were pooled to obtain standardised difference in means (SMD) with a 95% confidence interval. The search strategy identified 120 articles of which 7 trial assessing 883 subjects were included in the analysis. Systematic data support that Saccharomyces helps to relieve abdominal pain/discomfort (SMD = -0.205, P = 0.005), and presented potential improvements on psychological outcomes, stool form for IBS patients. It is hard to demonstrate favourable effects on other symptoms (including distension, mucus passage, sense of incomplete evacuation, urgency, straining). The incidence of mild complications ranged from 0 to 51.4%, but no serious complications were observed in the included trials. Therefore, the partial response and the relative safe of probiotic fungi for IBS treatment have been demonstrated from the existing trials. However, it is premature to eventually declare the practical effects of probiotic fungi. Conducting more high-quality and large-scale trials and real-world studies, or even developing new fungal strains, is still necessary.

[Spatial distribution of Oncomelania hupensis spread in Hubei Province from 2020 to 2022]

OBJECTIVE

To identify the spatial distribution pattern of Oncomelania hupensis spread in Hubei Province, so as to provide insights into precision O. hupensis snail control in the province.

METHODS

Data pertaining to emerging and reemerging snails were collected from Hubei Province from 2020 to 2022 to build a spatial database of O. hupensis snail spread. The spatial clustering of O. hupensis snail spread was identified using global and local spatial autocorrelation analyses, and the hot spots of snail spread were identified using kernel density estimation. In addition, the correlation between environments with snail spread and the distance from the Yangtze River was evaluated using nearest-neighbor analysis and Spearman correlation analysis.

RESULTS

O. hupensis snail spread mainly occurred along the Yangtze River and Jianghan Plain in Hubei Province from 2020 to 2022, with a total spread area of 4 320.63 hm2, including 1 230.77 hm2 emerging snail habitats and 3 089.87 hm2 reemerging snail habitats. Global spatial autocorrelation analysis showed spatial autocorrelation in the O. hupensis snail spread in Hubei Province in 2020 and 2021, appearing a spatial clustering pattern (Moran's I = 0.003 593 and 0.060 973, both P values < 0.05), and the mean density of spread snails showed spatial aggregation in Hubei Province in 2020 (Moran's I = 0.512 856, P < 0.05). Local spatial autocorrelation analysis showed that the high-high clustering areas of spread snails were mainly distributed in 50 settings of 10 counties (districts) in Hubei Province from 2020 to 2022, and the high-high clustering areas of the mean density of spread snails were predominantly found in 219 snail habitats in four counties of Jiangling, Honghu, Yangxin and Gong'an. Kernel density estimation showed that there were high-, secondary high- and medium-density hot spots in snail spread areas in Hubei Province from 2020 to 2022, which were distributed in Jingzhou District, Wuxue District, Honghu County and Huangzhou District, respectively. There were high- and medium-density hot spots in the mean density of spread snails, which were located in Jiangling County, Honghu County and Yangxin County, respectively. In addition, the snail spread areas negatively correlated with the distance from the Yangtze River (r = -0.108 9, P < 0.05).

CONCLUSIONS

There was spatial clustering of O. hupensis snail spread in Hubei Province from 2020 to 2022. The monitoring and control of O. hupensis snails require to be reinforced in the clustering areas, notably in inner embankments to prevent reemerging schistosomiasis.

Measurement of the Dependence of the Hadron Production Fraction Ratios f_{s}/f_{u} and f_{d}/f_{u} on B Meson Kinematic Variables in Proton-Proton Collisions at sqrt[s]=13 TeV

The dependence of the ratio between the B_{s}^{0} and B^{+} hadron production fractions, f_{s}/f_{u}, on the transverse momentum (p_{T}) and rapidity of the B mesons is studied using the decay channels B_{s}^{0}→J/ψϕ and B^{+}→J/ψK^{+}. The analysis uses a data sample of proton-proton collisions at a center-of-mass energy of 13 TeV, collected by the CMS experiment in 2018 and corresponding to an integrated luminosity of 61.6  fb^{-1}. The f_{s}/f_{u} ratio is observed to depend on the B p_{T} and to be consistent with becoming asymptotically constant at large p_{T}. No rapidity dependence is observed. The ratio of the B^{0} to B^{+} meson production fractions, f_{d}/f_{u}, is also measured, for the first time in proton-proton collisions, using the B^{0}→J/ψK^{*0} decay channel. The result is found to be within 1 standard deviation of unity and independent of p_{T} and rapidity, as expected from isospin invariance.

[Impact of different diagnostic criteria for assessing mild micro-hepatic encephalopathy in liver cirrhosis: an analysis based on a prospective, multicenter, real-world study]

Objective: To compare the differences in the prevalence of mild micro-hepatic encephalopathy (MHE) among patients with cirrhosis by using the psychometric hepatic encephalopathy score (PHES) and the Stroop smartphone application (Encephal App) test. Methods: This prospective, multi-center, real-world study was initiated by the National Clinical Medical Research Center for Infectious Diseases and the Portal Hypertension Alliance and registered with International ClinicalTrials.gov (NCT05140837). 354 cases of cirrhosis were enrolled in 19 hospitals across the country. PHES (including digital connection tests A and B, digital symbol tests, trajectory drawing tests, and serial management tests) and the Stroop test were conducted in all of them. PHES was differentiated using standard diagnostic criteria established by the two studies in China and South Korea. The Stroop test was evaluated based on the criteria of the research and development team. The impact of different diagnostic standards or methods on the incidence of MHE in patients with cirrhosis was analyzed. Data between groups were differentiated using the t-test, Mann-Whitney U test, and χ (2) test. A kappa test was used to compare the consistency between groups. Results: After PHES, the prevalence of MHE among 354 cases of cirrhosis was 78.53% and 15.25%, respectively, based on Chinese research standards and Korean research normal value standards. However, the prevalence of MHE was 56.78% based on the Stroop test, and the differences in pairwise comparisons among the three groups were statistically significant (kappa = -0.064, P < 0.001). Stratified analysis revealed that the MHE prevalence in three groups of patients with Child-Pugh classes A, B, and C was 74.14%, 83.33%, and 88.24%, respectively, according to the normal value standards of Chinese researchers, while the MHE prevalence rates in three groups of patients with Child-Pugh classes A, B, and C were 8.29%, 23.53%, and 38.24%, respectively, according to the normal value standards of Korean researchers. Furthermore, the prevalence rates of MHE in the three groups of patients with Child-Pugh grades A, B, and C were 52.68%, 58.82%, and 73.53%, respectively, according to the Stroop test standard. However, among the results of each diagnostic standard, the prevalence of MHE showed an increasing trend with an increasing Child-Pugh grade. Further comparison demonstrated that the scores obtained by the number connection test A and the number symbol test were consistent according to the normal value standards of the two studies in China and South Korea (Z = -0.982, -1.702; P = 0.326, 0.089), while the other three sub-tests had significant differences (P < 0.001). Conclusion: The prevalence rate of MHE in the cirrhotic population is high, but the prevalence of MHE obtained by using different diagnostic criteria or methods varies greatly. Therefore, in line with the current changes in demographics and disease spectrum, it is necessary to enroll a larger sample size of a healthy population as a control. Moreover, the establishment of more reliable diagnostic scoring criteria will serve as a basis for obtaining accurate MHE incidence and formulating diagnosis and treatment strategies in cirrhotic populations.

SKIN REINNERVATION BY COLLATERAL SPROUTING FOLLOWING SPARED NERVE INJURY IN MICE

Following peripheral nerve injury, denervated tissues can be reinnervated via regeneration of injured neurons or via collateral sprouting of neighboring uninjured afferents into the denervated territory. While there has been substantial focus on mechanisms underlying regeneration, collateral sprouting has received relatively less attention. In this study, we used immunohistochemistry and genetic neuronal labeling to define the subtype specificity of sprouting-mediated reinnervation of plantar hind paw skin in the mouse spared nerve injury (SNI) model, in which productive regeneration cannot occur. Following an initial loss of cutaneous afferents in the tibial nerve territory, we observed progressive centripetal reinnervation by multiple subtypes of neighboring uninjured fibers into denervated glabrous and hairy plantar skin. In addition to dermal reinnervation, CGRP-expressing peptidergic fibers slowly but continuously repopulated the denervated epidermis, Interestingly, GFRα2-expressing nonpeptidergic fibers exhibited a transient burst of epidermal reinnervation, followed by trend towards regression. Presumptive sympathetic nerve fibers also sprouted into the denervated territory, as did a population of myelinated TrkC lineage fibers, though the latter did so less efficiently. Conversely, rapidly adapting Aβ fiber and C fiber low threshold mechanoreceptor (LTMR) subtypes failed to exhibit convincing collateral sprouting up to 8 weeks after nerve injury. Optogenetics and behavioral assays further demonstrated the functionality of collaterally sprouted fibers in hairy plantar skin with restoration of punctate mechanosensation without hypersensitivity. Our findings advance understanding of differential collateral sprouting among sensory neuron subpopulations and may guide strategies to promote the progression of sensory recovery or limit maladaptive sensory phenomena after peripheral nerve injury.

Significance Statement

Following nerve injury, whereas one mechanism for tissue reinnervation is regeneration of injured neurons, another, less well studied mechanism is collateral sprouting of nearby uninjured neurons. In this study, we examined collateral sprouting in denervated mouse skin and showed that it involves some, but not all neuronal subtypes. Despite such heterogeneity, a significant degree of restoration of punctate mechanical sensitivity is achieved. These findings highlight the diversity of collateral sprouting among peripheral neuron subtypes and reveal important differences between pre- and post-denervation skin that might be appealing targets for therapeutic correction to enhance functional recovery from denervation and prevent unwanted sensory phenomena such as pain or numbness.

[Research progress of optical coherence tomography in the airway]

Optical coherence tomography (OCT) is a specialized optical imaging technique with a history of more than 30 years, known as'optical biopsy' because of its high resolution and high sensitivity. OCT has been used in the airway for more than 20 years, and researchers have explored and improved the imaging methods of OCT in the airway, focusing mainly on expanding the imaging site and enriching the imaging content. In terms of broadening the imaging site, it covers the airway from generation 0 to 9. In terms of enriching imaging content, additional assessment of airway wall blood vessels, airway smooth muscle, fibrous tissue, and airway compliance can be performed. It plays an important role in the study of various respiratory diseases. Therefore, this paper mainly summarized the exploration of the imaging site and content of airway OCT as follows.

[Epidemiological characteristics of reinfection of 2019-nCoV and influencing factors in Ningbo]

Objective: To analyze the epidemiological characteristics of reinfection of 2019-nCoV and influencing factors, and provide evidence for effective prevention and control of COVID-19 epidemic. Methods: The incidence data of COVID-19 in Ningbo from January 1, 2020 to November 30, 2022 were collected from the infectious disease surveillance system of Chinese information system for disease control and prevention. The incidence of reinfection of 2019-nCoV was investigated by using questionnaire. logistic regression analysis was used to analyze the influences of gender, age, time interval from the first infection, history of underlying disease, 2019-nCoV vaccination dose and disease severity on the reinfection. Results: A total of 897 previous 2019-nCoV infection cases were investigated, of which 115 experienced the reinfection of 2019-nCoV, the reinfection rate was 12.82%. The interval between the two infections M(Q1, Q3) was 1 052 (504, 1 056) days. Univariate analysis showed that age, 2019-nCoV vaccination dose, history of underlying disease, type of 2019-nCoV variant causing the first infection, time interval from the first infection and severity of the first infection were associated with the reinfection rate (all P<0.05). Multivariate logistic regression analysis showed that the risk for reinfection in age group 30- years was higher than that in age group ≥60 years (OR=2.10, 95%CI: 1.11-3.97). No reinfection occurred in those with time interval from the first infection of <6 months, and the risk for reinfection was higher in those with the time interval of ≥12 months than in those with the time interval of 6- months (OR=6.68, 95%CI: 3.46-12.90). The risk for reinfection was higher in the common or mild cases than in the asymptomatic cases (OR=2.64, 95%CI: 1.18-5.88; OR=2.79, 95%CI: 1.27-6.11). Conclusion: The time interval from the first infection was an important influencing factor for the reinfection of 2019-nCoV, and the probability of the reinfection within 6 months was low.

First Double-Differential Measurement of Kinematic Imbalance in Neutrino Interactions with the MicroBooNE Detector

We report the first measurement of flux-integrated double-differential quasielasticlike neutrino-argon cross sections, which have been made using the Booster Neutrino Beam and the MicroBooNE detector at Fermi National Accelerator Laboratory. The data are presented as a function of kinematic imbalance variables which are sensitive to nuclear ground-state distributions and hadronic reinteraction processes. We find that the measured cross sections in different phase-space regions are sensitive to different nuclear effects. Therefore, they enable the impact of specific nuclear effects on the neutrino-nucleus interaction to be isolated more completely than was possible using previous single-differential cross section measurements. Our results provide precision data to help test and improve neutrino-nucleus interaction models. They further support ongoing neutrino-oscillation studies by establishing phase-space regions where precise reaction modeling has already been achieved.

Search for Exotic Higgs Boson Decays H→AA→4γ with Events Containing Two Merged Diphotons in Proton-Proton Collisions at sqrt[s]=13 TeV

We present the first direct search for exotic Higgs boson decays H→AA, A→γγ in events with two photonlike objects. The hypothetical particle A is a low-mass spin-0 particle decaying promptly to a merged diphoton reconstructed as a single photonlike object. We analyze the data collected by the CMS experiment at sqrt[s]=13  TeV corresponding to an integrated luminosity of 136  fb^{-1}. No excess above the estimated background is found. We set upper limits on the branching fraction B(H→AA→4γ) of (0.9-3.3)×10^{-3} at 95% confidence level for masses of A in the range 0.1-1.2 GeV.

Learning Intention-Aware Policies in Deep Reinforcement Learning

Deep reinforcement learning (DRL) provides an agent with an optimal policy so as to maximize the cumulative rewards. The policy defined in DRL mainly depends on the state, historical memory, and policy model parameters. However, we humans usually take actions according to our own intentions, such as moving fast or slow, besides the elements included in the traditional policy models. In order to make the action-choosing mechanism more similar to humans and make the agent to select actions that incorporate intentions, we propose an intention-aware policy learning method in this letter To formalize this process, we first define an intention-aware policy by incorporating the intention information into the policy model, which is learned by maximizing the cumulative rewards with the mutual information (MI) between the intention and the action. Then we derive an approximation of the MI objective that can be optimized efficiently. Finally, we demonstrate the effectiveness of the intention-aware policy in the classical MuJoCo control task and the multigoal continuous chain walking task.

Development in biomarkers of breast cancer: a bibliometric analysis from 2011 to 2020

OBJECTIVE

Breast cancer (BC) is a prevalent cancer all over the world. We conducted a bibliometric study to analyze global scientific results over the past 10 years, including the hotspots and frontiers of biomarker research in BC.

MATERIALS AND METHODS

From 2011 to 2020, literature research from the Web of Science Core Collection (WoSCC) was performed. VOSviewer was applied to analyze and visualize the frontiers and hotspots related to biomarker research in BC.

RESULTS

13,680 papers were retrieved. There was an increasing number of annual publications (Np) related to biomarkers in BC during the past decade. The United States (US) published the greatest number of papers, which had the highest number of citations (Nc) and ranked first in terms of H-index. PLoS One and the University of Texas System were the most productive journals and affiliations, respectively. In 2014, Chetan Bettegowda published a paper with the world's highest global citation score (GCS). In recent years, keywords such as "expression", "microRNA", and "cell" have appeared most frequently. In addition, research related to COVID-19 in this field has become a hot topic in recent years. This bibliometric study found an increasing trend in publications related to biomarkers in British Columbia and the US was found to be an influential producer in this field.

CONCLUSIONS

In the past decade, most research has focused on basic and clinical studies, of which microRNAs (miRNAs) and circulating tumor DNAs (ctDNAs) associated with the inhibition and attenuation of BC have become the focus of recent research.

Single-step genome-wide association for selected milk fatty acids in Dual-Purpose Belgian Blue cows

The aim of this study was to estimate genetic parameters and identify genomic regions associated with selected individual and groups of milk fatty acids (FA) predicted by milk mid-infrared spectrometry in Dual-Purpose Belgian Blue cows. The used data were 69,349 test-day records of milk yield, fat percentage, and protein percentage along with selected individual and groups FA of milk (g/dL milk) collected from 2007 to 2020 on 7,392 first-parity (40,903 test-day records), and 5,185 second-parity (28,446 test-day records) cows distributed in 104 herds in the Walloon Region of Belgium. Data of 28,466 SNPs, located on 29 Bos taurus autosomes (BTA), of 1,699 animals (639 males and 1,060 females) were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic best linear unbiased prediction approach. The proportion of genetic variance explained by each 25-SNP sliding window (with an average size of ~2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Average daily heritability estimated for the included milk FA traits ranged from 0.01 (C4:0) to 0.48 (C12:0) and 0.01 (C4:0) to 0.42 (C12:0) in the first and second parities, respectively. Genetic correlations found between milk yield and the studied individual milk FA, except for C18:0, C18:1 trans, C18:1 cis-9, were positive. The results showed that fat percentage and protein percentage were positively genetically correlated with all studied individual milk FA. Genome-wide association analyses identified 11 genomic regions distributed over 8 chromosomes [BTA1, BTA4, BTA10, BTA14 (4 regions), BTA19, BTA22, BTA24, and BTA26] associated with the studied FA traits, though those found on BTA14 partly overlapped. The genomic regions identified differed between parities and lactation stages. Although these differences in genomic regions detected may be due to the power of quantitative trait locus detection, it also suggests that candidate genes underlie the phenotypic expression of the studied traits may vary between parities and lactation stages. These findings increase our understanding about the genetic background of milk FA and can be used for the future implementation of genomic evaluation to improve milk FA profile in Dual-Purpose Belgian Blue cows.