[Role of neoadjuvant rectal score in prognosis and adjuvant chemotherapy decision-making in locally advanced rectal cancer following neoadjuvant short-course radiotherapy and consolidation chemotherapy]

Objectives: To assess the prognostic impact of the neoadjuvant rectal (NAR) score following neoadjuvant short-course radiotherapy and consolidation chemotherapy in locally advanced rectal cancer (LARC), as well as its value in guiding decisions for adjuvant chemotherapy. Methods: Between August 2015 and August 2018, patients were eligible from the STELLAR phase III trial (NCT02533271) who received short-course radiotherapy plus consolidation chemotherapy and for whom the NAR score could be calculated. Based on the NAR score, patients were categorized into low (＜8), intermediate (8-16), and high (＞16) groups. The Kaplan-Meier method, log rank tests, and multivariate Cox proportional hazard regression models were used to evaluate the impact of the NAR score on disease-free survival (DFS). Results: Out of the 232 patients, 24.1%, 48.7%, and 27.2% had low (56 cases), intermediate (113 cases), and high NAR scores (63 cases), respectively. The median follow-up period was 37 months, with 3-year DFS rates of 87.3%, 68.3%, and 53.4% (P＜0.001) for the low, intermediate, and high NAR score groups. Multivariate analysis demonstrated that the NAR score (intermediate NAR score: HR, 3.10, 95% CI, 1.30-7.37, P=0.011; high NAR scores: HR=5.44, 95% CI, 2.26-13.09, P＜0.001), resection status (HR, 3.00, 95% CI, 1.64-5.52, P＜0.001), and adjuvant chemotherapy (HR, 3.25, 95% CI, 2.01-5.27, P＜0.001) were independent prognostic factors for DFS. In patients with R0 resection, the 3-year DFS rates were 97.8% and 78.0% for those with low and intermediate NAR scores who received adjuvant chemotherapy, significantly higher than the 43.2% and 50.6% for those who did not (P＜0.001, P=0.002). There was no significant difference in the 3-year DFS rate (54.2% vs 53.3%, P=0.214) among high NAR score patients, regardless of adjuvant chemotherapy. Conclusions: The NAR score is a robust prognostic indicator in LARC following neoadjuvant short-course radiotherapy and consolidation chemotherapy, with potential implications for subsequent decisions regarding adjuvant chemotherapy. These findings warrant further validation in studies with larger sample sizes.

Effects of anodic transcranial direct current stimulation combined with physical training on the performance of elite swimmers

Objective

Anodal transcranial direct current stimulation (a-tDCS) has been used to improve athletic performance in various populations; however, its role in improving performance in elite athletes is unclear. This study aimed to investigate the effects of a-tDCS on athletic performance in elite athletes.

Methods

We used a single-blind, randomized controlled experimental design and recruited 24 national-level freestyle swimmers from China. All athletes were randomly divided into two groups; the experimental group underwent a-tDCS (current 2 mA for 20 min) combined with physical training, and the control group underwent a-tDCS sham stimulation combined with physical training. The physical training program was identical in the experimental and control groups. The intervention period was 6 weeks, with five weekly sessions of 110 min each, consisting of 20 min of a-tDCS and 90 min of physical training. Base strength, explosive strength, aerobic endurance, and anaerobic endurance were measured in the athletes before and after the intervention.

Results

The results were as follows. 1) Basic strength: There was a significant improvement in 5RM pull-ups in the experimental and control groups before and after the intervention (p < 0.05). 2) Explosive strength: There was a significant improvement in vertical jump and swimming start distance into the water in the experimental and control groups before and after the intervention (p < 0.05). 3) Aerobic endurance: There was no significant improvement in the experimental and control groups before and after the intervention. 4) Anaerobic endurance: There was a significant improvement in 400 m running performance in the experimental and control groups before and after the intervention (p < 0.05).

Conclusion

Compared to physical training alone, a-tDCS combined with physical training can better improve the athletic performance of high-level swimmers, especially in basic strength, explosive strength, and aerobic endurance.

[Prediction of prognosis of patients with radical resection of intrahepatic cholangiocarcinoma based on single cell omics]

Objectives: To analyze the survival benefit of intrahepatic cholangiocarcinoma (ICC) radical resection based on single cell omics. Methods: This is a retrospective case-series study. ICC single-cell sequencing was integrated from four data sets in the Gene Expression Omnibus Database, with a total of 46 patients undergoing radical resection, to explore the characteristics of the microenvironment. Microarray data of 100 ICC cases was analyzed in the EMBI database with survival data. The infiltration abundance of each epithelial cell cluster was calculated in each microarray data sample using the ssGSEA algorithm. The key epithelial cell cluster associated with poor patient outcomes was explored. The clinical value of key marker genes in this subgroup was studied. Prognostic marker genes were selected using the univariate and multivariate Cox proportional hazards(CoxPH) model. The The CoxPH model was constructed by the target genes and a nomogram was drawn. Kaplan-Meier survival analysis was used to verify the relationship between score and prognosis of patients. The predictive power of the model was evaluated by receiver operating characteristic(ROC) curves, calibration curves, and decision curve analysis (DCA). Results: Epithelial cell clusters infiltrated almost exclusively in tumor tissue. The MT2A+ epithelial cell subset was associated with a poorer prognosis for patients with a high invasion abundance and patients characterized by infiltration of this group were defined as antioxidant. After screening marker genes in this cluster using a univariate and multivariate CoxPH model, the following genes were found to be independent prognostic factors: FILPIL, NFKBIA, PEG10, SERPINB5. The CoxPH model was constructed using the four gene expression levels, and the survival rate of patients in the high-risk group was significantly lower than those in the low-risk group (all P<0.05). The constructed nomogram had good discrimination and validity. The ROC curve showed that the predicted area under the curve was 0.779, 0.844 and 0.845 at 1, 3 and 5 years, respectively. Compared to clinical indicators, the model had better predictive power using the calibration curve and the DCA test. Conclusions: The MT2A+ epithelial cell group may be associated with the prognosis of patients with ICC, and the concept of ICC tissue typing of antioxidant and non-antioxidant types is proposed. The type of antioxidant may predict the poor prognosis of the patients, and postoperative adjuvant therapy and other means could be considered to improve the survival of the patients.

[New advances in the diagnosis and treatment of intrahepatic cholangiocarcinoma]

Intrahepatic cholangiocarcinoma (ICC) is a type of primary liver cancer, which has shown an increasing trend in incidence and mortality in recent years, with a poor prognosis. The clinical diagnosis and treatment of ICC currently face the challenges of low detection rate, high mortality rate, poor treatment outcome, and urgently need more in-depth research to promote the improvement of clinical diagnosis and treatment level. In recent years, ICC diagnosis and treatment related research has made new progress in many aspects, and the knowledge about these new clinical diagnosis and treatment advances should be updated in a timely manner. This article reviewed the latest research results in recent years, summarized some new views on ICC typing, prevention and diagnosis staging that have been proposed recently, as well as the new progress made in surgical treatment and systemic treatment, and briefly discussed the potential of ICC individualized precision treatment and the occurrence of rare complications caused by combined treatment.

Clinical and radiographic outcomes of a combined surgery approach to treat peri-implantitis

Peri-implant infra-bony defects are difficult to treat, and data on the management of peri-implantitis are lacking. The aim of this study was to evaluate the effect of a combined surgical approach to manage peri-implantitis: implantoplasty with xenogeneic bone grafting and a concentrated growth factor membrane. Two independent examiners analysed the medical records and radiographs taken before surgery and at the last follow-up. Data were analysed at the implant level; some patient-level data (age, sex, smoking habit) were also considered. Linear regression analysis with generalized estimating equations (GEE) was used to explore the effect of variables of interest (including marginal bone level (MBL)) on implantitis treatment success and resolution rates. The effect of the prosthesis type on postoperative clinical and radiographic parameters was also explored by GEE, with adjustment for age, sex, tooth site, location, follow-up duration, and implant length (model IV including all). Thirty patients with 72 implants were investigated. The implant survival rate was 100% over a mean observation period of 3.3 years (range 2-11 years). The treatment success rate (bone loss <0.5 mm, no bleeding on probing (BOP), no suppuration, probing depth (PD) < 5 mm) was higher in females than males (50% vs 19.0%; P = 0.008). At the last postoperative follow-up, the MBL (1.51 ± 1.07 vs 4.01 ± 1.13 mm), PD (3.61 ± 0.84 vs 6.54 ± 1.01 mm), and BOP (23.38 ± 23.18% vs 79.17 ± 15.51%) were significantly reduced when compared to pre-surgery values (all P < 0.001). Furthermore, a significantly higher PD reduction (β = -1.10 mm, 95% confidence interval -1.97 to -0.23 mm, P = 0.014) was observed for implants with a single crown than a full-arch prosthesis (GEE model IV). Preliminary clinical and radiographic data indicate that implantoplasty in combination with surgery could be an effective treatment option for peri-implantitis.

Deep conditional generative model for longitudinal single-slice abdominal computed tomography harmonization

Purpose

Two-dimensional single-slice abdominal computed tomography (CT) provides a detailed tissue map with high resolution allowing quantitative characterization of relationships between health conditions and aging. However, longitudinal analysis of body composition changes using these scans is difficult due to positional variation between slices acquired in different years, which leads to different organs/tissues being captured.

Approach

To address this issue, we propose C-SliceGen, which takes an arbitrary axial slice in the abdominal region as a condition and generates a pre-defined vertebral level slice by estimating structural changes in the latent space.

Results

Our experiments on 2608 volumetric CT data from two in-house datasets and 50 subjects from the 2015 Multi-Atlas Abdomen Labeling Challenge Beyond the Cranial Vault (BTCV) dataset demonstrate that our model can generate high-quality images that are realistic and similar. We further evaluate our method's capability to harmonize longitudinal positional variation on 1033 subjects from the Baltimore longitudinal study of aging dataset, which contains longitudinal single abdominal slices, and confirmed that our method can harmonize the slice positional variance in terms of visceral fat area.

Conclusion

This approach provides a promising direction for mapping slices from different vertebral levels to a target slice and reducing positional variance for single-slice longitudinal analysis. The source code is available at: https://github.com/MASILab/C-SliceGen.

[Observation of the consistency between intellectualized and manual-based cognitive assessment tools in the outpatient clinic]

Objective: The intellectualized versions of the Montreal Cognitive Assessment Scale (MoCA) and the Mini-mental State Examination (MMSE) (i-MoCA/i-MMSE) were developed. The validity of this system was evaluated in a clinical sample through comparing with the manual-based assessments. Methods: A total of 88 patients [aged (66.82±11.37) years, 30 males and 58 females] were enrolled in the outpatient clinic of Xuanwu Hospital of Capital Medical University with complaints of cognitive decline, from February to October 2023. All participants completed manual-based and intellectualized assessments in a randomized order, with an interval of 2 weeks to control for the practice effect. The reliability of the intellectualized version of assessments was evaluated based on the manual-based version using the Concordance correlation coefficient (CCC). The difference between the intellectualized and the manual-based assessments was tested by the Repeated ANCOVA with demographic information controlled. The accuracy of evaluation of the i-MoCA and i-MMSE was analyzed by the Receiver Operating Characteristic (ROC) analysis. Results: High concordance was observed between the intellectualized version and the manual-based assessments (CCCMoCA=0.87, CCCMMSE=0.83). Controlling for basic demographic information, there was no significant difference in the scores of the intellectualized version and the manual-based assessments (all P>0.05). The accuracy of i-MoCA in screening patients with cognitive impairment was 94.3% (sensitivity=94.6%, specificity=78.1%), while the accuracy of i-MMSE in screening patients with cognitive impairment was 94.9% (sensitivity=94.9%, specificity=77.6%). In addition, the majority of subdomains measured by the cognitive assessments exhibited high consistency across the intellectualized the manual-based versions (CCCMoCA=0.32-0.78; CCCMMSE=0.54-0.79). Conclusion: Both the i-MoCA and i-MMSE showed high consistency and diagnostic accuracy with the manual-based versions in terms of overall cognitive function and subdomains.

Effects of low-volume functional and running high-intensity interval training on physical fitness in young adults with overweight/obesity

Objectives: This study examined and compared the effects of functional and running high-intensity interval training (HIIT) on body composition, cardiorespiratory fitness, and muscular fitness of young adults with overweight or obesity. Methods: Forty-five participants (22.1 ± 2.1 years, BMI = 25.2 ± 1.0 kg/m2) were assigned to functional HIIT (HIIT-F; n = 15), running HIIT (HIIT-R; n = 15), or non-training control group (CON; n = 15). Participants in HIIT-F and HIIT-R performed functional exercise based-HIIT (four sets of all-out whole-body exercises including jumping jacks, squats, twist jumps and mountain climbers, et al.) and running HIIT (four sets of running on a treadmill) for 12 weeks, respectively. Body composition, muscular fitness, and cardiorespiratory fitness were assessed pre and post intervention. Results: Both HIIT-F and HIIT-R significantly improved the body composition and cardiorespiratory fitness, with HIIT-F induced greater improvements in lean mass (+1.623 vs. -1.034 kg, p < 0.001), back strength (+6.007 vs. +3.333 kg, p < 0.01), and push-ups (+5.692 vs. 1.923 reps, p < 0.001) than that in HIIT-R. HIIT-R reduced more visceral fat area (VFA) (-11.416 vs. -4.338 cm2, p = 0.052) and induced similar improvement in cardiorespiratory fitness (VO2max, +2.192 vs. +2.885 mL/kg/min, p = 0.792) with HIIT-F. Conclusion: Twelve weeks of HIIT-R or HIIT-F improved physical fitness among young adults with overweight or obesity. Despite the similar impact on cardiorespiratory fitness, HIIT-F generates a better positive effect on muscular fitness relative to HIIT-R, which could be partly explained by the greater increase in lean mass after HIIT-F intervention.

UNesT: Local spatial representation learning with hierarchical transformer for efficient medical segmentation

Transformer-based models, capable of learning better global dependencies, have recently demonstrated exceptional representation learning capabilities in computer vision and medical image analysis. Transformer reformats the image into separate patches and realizes global communication via the self-attention mechanism. However, positional information between patches is hard to preserve in such 1D sequences, and loss of it can lead to sub-optimal performance when dealing with large amounts of heterogeneous tissues of various sizes in 3D medical image segmentation. Additionally, current methods are not robust and efficient for heavy-duty medical segmentation tasks such as predicting a large number of tissue classes or modeling globally inter-connected tissue structures. To address such challenges and inspired by the nested hierarchical structures in vision transformer, we proposed a novel 3D medical image segmentation method (UNesT), employing a simplified and faster-converging transformer encoder design that achieves local communication among spatially adjacent patch sequences by aggregating them hierarchically. We extensively validate our method on multiple challenging datasets, consisting of multiple modalities, anatomies, and a wide range of tissue classes, including 133 structures in the brain, 14 organs in the abdomen, 4 hierarchical components in the kidneys, inter-connected kidney tumors and brain tumors. We show that UNesT consistently achieves state-of-the-art performance and evaluate its generalizability and data efficiency. Particularly, the model achieves whole brain segmentation task complete ROI with 133 tissue classes in a single network, outperforming prior state-of-the-art method SLANT27 ensembled with 27 networks. Our model performance increases the mean DSC score of the publicly available Colin and CANDI dataset from 0.7264 to 0.7444 and from 0.6968 to 0.7025, respectively. Code, pre-trained models, and use case pipeline are available at: https://github.com/MASILab/UNesT.

New approaches in the diagnosis and prognosis of gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is the most common pregnancy metabolic disorder in which a person with no history of hyperglycemia exhibits any degree of impaired glucose tolerance during gestation. GDM can be resolved on its own after birth, but mothers with GDM are more at risk for future problems, such as type 2 diabetes, obesity, and cardiovascular disease. In addition, GDM can cause macrosomia in infants and obesity or even the risk of diabetes in childhood. Standard diagnostic tests for GDM are the oral glucose tolerance test (OGTT) and glucose challenge test (GCT), which is a mandatory test at 28-28 weeks of pregnancy in most countries. Disorders in various molecular mechanisms, such as hepatocyte growth factor (HGF), mechanistic target of rapamycin (mTOR), and nuclear factor-kappaB (NF-κB) signaling pathways are involved in GDM. Therefore, a better understanding of these mechanisms can help find new therapeutic and diagnostic strategies accordingly. In this review, we first deal with molecular mechanisms involved in GDM occurrence and then summarized the studies that hired this knowledge for early diagnosis and prognosis of GDM. Finally, we present the latest achievements in the diagnosis of GDM based on exosomes, microRNAs, glycosylated hemoglobin, and inflammatory factors detection in maternal circulation.

Using SNP addresses for Salmonella Typhimurium DT104 in routine veterinary outbreak detection

SNP addresses are a pathogen typing method based on whole-genome sequences (WGSs), assigning groups at seven different levels of genetic similarity. Public health surveillance uses it for several gastro-intestinal infections; this work trialled its use in veterinary surveillance for salmonella outbreak detection. Comparisons were made between temporal and spatio-temporal cluster detection models that either defined cases by their SNP address or by phage type, using historical data sets. Clusters of SNP incidents were effectively detected by both methods, but spatio-temporal models consistently detected these clusters earlier than the corresponding temporal models. Unlike phage type, SNP addresses appeared spatially and temporally limited, which facilitated the differentiation of novel, stable, or expanding clusters in spatio-temporal models. Furthermore, these models flagged spatio-temporal clusters containing only two to three cases at first detection, compared with a median of seven cases in phage-type models. The large number of SNP addresses will require automated methods to implement these detection models routinely. Further work is required to explore how temporal changes and different host species may impact the sensitivity and specificity of cluster detection. In conclusion, given validation with more sequencing data, SNP addresses are likely to be a valuable addition to early warning systems in veterinary surveillance.

[Human amniotic membrane plug for recurrent retinal detachment associated with pathologic myopic macular hole]

A 60-year-old woman presented with a history of "pathological myopia combined with macular hole retinal detachment, " for which she underwent vitrectomy, internal limiting membrane tamponade, and silicone oil filling surgery one year ago. Seven months ago, the silicone oil was removed. She now returned to seek medical attention as her visual acuity has declined by 10 diopters. Examination revealed a recurrence of macular hole retinal detachment. The patient was treated with combined amniotic membrane tamponade and silicone oil filling. During the surgery, the frozen amniotic membrane was cut into 2 mm × 2 mm and placed under the macular hole retina after silicone oil filling. Within 6 months after the surgery, her retina repositioned well, the macular hole closed, and her visual function improved from hand motion to 0.05. No severe complications were observed. Therefore, this surgical approach provides a new perspective for treating recurrent pathological myopia combined with macular hole retinal detachment.

The economic burden of coronary heart disease in mainland China

OBJECTIVES

The aim of this study was to systematically evaluate the current economic burden of coronary heart disease (CHD) in mainland China and provide a reference for the formulation of policies to reduce the economic burden of CHD.

STUDY DESIGN

A systematic literature review was conducted of empirical studies on the economic burden of CHD over the past 20 years.

METHODS

PubMed, Web of Science, Embase, China Knowledge Resource Integrated Database and the WANFANG database were comprehensively searched for relevant articles published between 1 January 2000 and 22 December 2021. Content analysis was used to extract the data, and Stata 17.0 software was used for analysis. The median values were used to describe trends.

RESULTS

A total of 35 studies were included in this review. The annual median per-capita hospitalisation expense and the average expense per hospitalisation were $3544.40 ($891.64-$18,371.46) and $5407.34 ($1139.93-$8277.55), respectively. The median ratio on medical consumables expenses, drug expenses, medical examination expenses and treatment expenses were 41.59% (12.40%-63.73%), 26.90% (7.30%-60.00%), 9.45% (1.65%-33.40%) and 10.10% (2.36%-66.00%), respectively. The median per-capita hospitalisation expense in the eastern, central and western regions were $9374.45 ($2056.13-$18,371.46), $4751.5 ($2951.95-$8768.93) and $3251.25 ($891.64-$13,986.38), respectively. The median average expense per hospitalisation in the eastern and central regions were $6177.15 ($1679.15-$8277.55) and $1285.49 ($1239.93-$2197.36), respectively. The median average length of stay in the eastern, central and western regions were 9.3 days, 15.2 days and 16.1 days, respectively.

CONCLUSIONS

The economic burden of CHD is more severe in mainland China than in developed countries, especially in terms of the direct economic burden. In terms of the types of direct medical expenses, a proportion of medical examination expenses, treatment expenses and drug expenses were lowest in the eastern region, but medical consumables expenses were the highest in this region. This study provides guidance for the formulation of policies to reduce the economic burden of CHD in mainland China.

Prognostic Role and Time Varying Failure Hazard of Neoadjuvant Rectal (NAR) Scores in the Stellar Randomized Phase 3 Trial

PURPOSE/OBJECTIVE(S)

This study examined the prognostic role of the neoadjuvant rectal (NAR) score on disease-free survival (DFS) in the STELLAR phase III trial and assessed time-varying failure hazard.

MATERIALS/METHODS

The study included patients from the STELLAR trial who underwent total mesorecta excision and had calculable NAR scores. Chi-square tests were used to analyze the distribution of demographic information, treatment information, and NAR scores. Kaplan-Meier and Cox regression analyses assessed DFS, while smoothed hazard plots evaluated hazard variations.

RESULTS

Of 461 patients, 231 received total neoadjuvant therapy (TNT) and 229 received concurrent chemoradiotherapy (CRT). With a median follow-up of 37 months, 3-year DFS rates for low, intermediate, and high NAR scores were 86.2%, 72.671.8%, and 53.153.6%, respectively (P <0.001). In the TNT group, rates for the corresponding NAR score groups were 87.3%, 67.6%, and 52.4% while in the CRT group, rates were 84.7%, 76.0%, and 53.4% (both P <0.001). Multivariate analysis showed NAR scores as independent prognostic factors for DFS (intermediate vs. low, hazard ratio (HR) = 2.452.55, 95% confidence interval (CI): 1.347 - 4.4675, P <0.003; high vs. low, HR = 4.2668, 95% CI: 2.5133 - 8.727.79, P <0.001). The DFS hazardrisk rates for different NAR score groups initially increased and then decreased, peaking in the second year with rates of 5.04.6%, 11.62%, and 21.52% for low, intermediate, and high NAR scores, respectively. After the fourth year, the high NAR score still had a higher failure hazardrisk (12.5%), while the intermediate and low NAR score had a lower relapse hazardrisk (<3%).

CONCLUSION

The NAR score was a strong prognostic factor for DFS in the STELLAR trial, irrespective of TNT or CRT modalities. Hazard variations at different NAR score levels offer insights for personalized monitoring and warrant further investigation in clinical trials using NAR scores as endpoints. (NCT02533271).

Democratizing Pathological Image Segmentation with Lay Annotators via Molecular-empowered Learning

Multi-class cell segmentation in high-resolution Giga-pixel whole slide images (WSI) is critical for various clinical applications. Training such an AI model typically requires labor-intensive pixel-wise manual annotation from experienced domain experts (e.g., pathologists). Moreover, such annotation is error-prone when differentiating fine-grained cell types (e.g., podocyte and mesangial cells) via the naked human eye. In this study, we assess the feasibility of democratizing pathological AI deployment by only using lay annotators (annotators without medical domain knowledge). The contribution of this paper is threefold: (1) We proposed a molecular-empowered learning scheme for multi-class cell segmentation using partial labels from lay annotators; (2) The proposed method integrated Giga-pixel level molecular-morphology cross-modality registration, molecular-informed annotation, and molecular-oriented segmentation model, so as to achieve significantly superior performance via 3 lay annotators as compared with 2 experienced pathologists; (3) A deep corrective learning (learning with imperfect label) method is proposed to further improve the segmentation performance using partially annotated noisy data. From the experimental results, our learning method achieved F1 = 0.8496 using molecular-informed annotations from lay annotators, which is better than conventional morphology-based annotations (F1 = 0.7015) from experienced pathologists. Our method democratizes the development of a pathological segmentation deep model to the lay annotator level, which consequently scales up the learning process similar to a non-medical computer vision task. The official implementation and cell annotations are publicly available at https://github.com/hrlblab/MolecularEL.

Methodological and Reporting Quality of Non-Inferiority or Equivalence Designs: A Systematic Review of Trial Characteristics, Design Consideration and Interpretation in Breast Cancer Radiotherapy Trials

PURPOSE/OBJECTIVE(S)

To investigate the methodological and reporting quality of non-inferiority (NI)/equivalence trials of breast cancer radiotherapy and to provide suggestions for future NI/equivalence trials.

MATERIALS/METHODS

Prospective phase III randomized controlled trials (RCTs) comparing different radiation modalities in patients with breast cancer and designed or interpreted as NI/equivalence were identified in PubMed, EMBASE and Cochrane library. Two reviewers independently extracted data on trial characteristics, statistical design assumptions and analysis considerations, primary end point results and conclusions. The relationship between the number of published trials and the year of publication was assessed by simple linear regression. Trials with pre-specified NI margins as absolute risk differences were reevaluated using margins as relative risk differences.

RESULTS

A total of 1490 records were screened and 41 articles published between January 1, 2001 and May 9, 2022 were selected for full text review. A total of 21 trials were included (18 designed as NI and 3 as equivalence). Publication of these trials increased over time (p = 0.023). Trial interventions included dose fractionation (n = 10), partial/whole breast irradiation (n = 8) and tumor bed boost (n = 3). Eleven (52.4%) trials clearly described the non-efficacy benefits. The primary endpoints included 5-year local recurrence (LR) (n = 11), 5-year locoregional recurrence (n = 3), acute/late toxicities (n = 5), 2-year LR and cosmetic outcome (n = 1), and 10-year LR (n = 1). Only seven (33.3%) trials provided justification of the margins. The absolute and relative risk margins were both mentioned in nine (42.9%) trials' methods and reported in six (28.6%) trials' results. The analyzed populations were intention-to-treat (ITT) in 10, both ITT and per-protocol in 9 trials. Seventeen (81%) trials reported confidence interval (CI), with twelve reporting CI that agreed with the type I error used in sample size calculation, but only eight (38.1%) reported p value for NI/equivalence test. Fifteen (71.4%) trials concluded NI/equivalence. Five (23.8%) trials had misleading conclusions (four for not mentioning small sample size insufficient to confirm NI/equivalence and one for inconsistent with the published results). Thirteen (61.9%) trials reported that the protocol's initial accrual target was not met, with ten (47.6%) owing to overestimation of event rates. For trials that met NI only based on absolute margin, three of eight (37.5%) trials were classified as inconclusive with the assumed relative margins.

CONCLUSION

The use of NI/equivalence trials of breast cancer radiotherapy has dramatically increased recently, but there is substantial room for improvement in the methodological and reporting quality of NI/equivalence trials.

Comparison of Supraclavicular Surgery plus Radiotherapy vs. Radiotherapy Alone in Breast Cancer Patients with Synchronous Ipsilateral Supraclavicular Lymph Node Metastasis: A Multicenter Retrospective Study

PURPOSE/OBJECTIVE(S)

To evaluate and compare the outcomes of supraclavicular lymph node dissection (SLND) plus radiotherapy (RT) and RT alone for patients with synchronous ipsilateral supraclavicular lymph node metastasis (sISLM).

MATERIALS/METHODS

In all, 293 patients with sISLM across three centers were included. Of these, 85 (29.0%) received SLND plus RT and 208 (71.0%) received RT alone. All patients received preoperative systemic therapy followed by mastectomy or lumpectomy and axillary dissection. Supraclavicular recurrence-free survival (SCRFS), locoregional recurrence-free survival (LRRFS), distant metastasis-free survival (DMFS), disease-free survival (DFS), and overall survival (OS) were evaluated by using the Kaplan-Meier method and multivariate Cox models. Multiple imputation was used for missing data.

RESULTS

The median follow-up duration of the RT and SLND+RT groups were 53.7 and 63.5 months, respectively. For the RT and SLND+RT groups, the 5-year SCRFS rates were 91.7% vs. 85.5% (P = 0.522), LRRFS rates were 79.1% vs. 73.1% (P = 0.412), DMFS rates were 60.4 vs. 58.8% (P = 0.708), DFS rates were 57.6% vs. 49.7% (P = 0.291), and OS rates were 71.9% vs. 62.2% (P = 0.272), respectively. There was no significant effect on any outcome when comparing SLND+RT versus RT alone in the multivariate analysis. Based on four risk factors of DFS, patients were classified into three risk groups: the intermediate- and high-risk groups had significantly lower survival outcomes than the low-risk group. SLND+RT did not improve outcomes of any risk group compared with RT alone.

CONCLUSION

Patients with sISLM may not benefit from SLND. Distant metastasis remained the major failure pattern, especially for intermediate- and high-risk groups with sISLM may not benefit from SLND. Distant metastasis remained the major failure pattern, especially for intermediate- and high-risk groups.

Early Cardiotoxicity in Patients Receiving Hypofractionated Radiotherapy after Breast Conserving Surgery: Analysis of a Prospective Study

PURPOSE/OBJECTIVE(S)

To evaluate the early cardiotoxicity of hypofractionated radiotherapy (HFRT) in patients with left-sided breast cancer after breast-conserving surgery, and to investigate the correlation between cardiotoxicity and cardiac dose.

MATERIALS/METHODS

A total of 103 women from 2017 to 2018 who received left-sided whole-breast with or without regional nodal irradiation either using deep inspiration breath-hold (DIBH) or free-breathing (FB) technique were prospectively enrolled. N-terminal pro-B-type natriuretic peptide (NT-proBNP), electrocardiogram, and radionuclide myocardial perfusion imaging were conducted before and after HFRT. Logistic regression analyses were performed to determine the association of cancer treatment, cardiac dose, and cardiovascular risk factors with cardiotoxic effects.

RESULTS

The mean dose (Dmean) of the heart, left anterior descending coronary artery (LAD), left ventricular (LV), and right ventricular (RV) in all patients was 403 cGy, 1685 cGy, 627 cGy, and 444 cGy, respectively. In comparison to FB, DIBH significantly reduced cardiac dose (heart Dmean 250 cGy vs. 570 cGy, LAD Dmean 1250 cGy vs. 2170 cGy, LV Dmean 420 cGy vs. 850 cGy, RV Dmean 260 cGy vs. 650 cGy; all p<0.001). With a median follow-up of 49 months (range, 2-65 months), no patients had clinical cardiac abnormalities or cardiac-related symptoms, but 42 (41%) patients had subclinical cardiac events. Among them, 41 were electrocardiogram changes, and one had LV ejection fraction decreased by 10% compared with the baseline level. Twenty-five (60%) recovered during follow-up, of which 17 (40%) experienced subclinical changes only once. The mean value of NT-proBNP did not change significantly before and after HFRT. In univariate analyses, DIBH technique significantly decreased the risk of subclinical cardiac events compared with FB (OR 0.31, 95% CI 0.14-0.71; p = 0.006); however, higher mean doses of heart and LV, anthracycline-based chemotherapy, obesity, and hypertension were associated with increased risk of subclinical cardiac events (all p<0.05).

CONCLUSION

Early subclinical cardiac damage after HFRT in left-sided breast cancer is dose-related, and mostly manageable and reversible without medical intervention.

Adaptive Ultra-Hypofractionated Whole-Pelvic Radiotherapy in High-Risk and Very High-Risk Prostate Cancer on 1.5-1.5 MR Linac: The Estimated Delivered Dose and Early Toxicity Results

PURPOSE/OBJECTIVE(S)

To study the feasibility and safety for patients with high-risk (HR) and very high-risk (VHR) prostate cancer treated with adaptive ultra-hypofractionated whole-pelvic radiotherapy (UHF-WPRT) on 1.5 magnetic resonance (MR)-Linac.

MATERIALS/METHODS

Sevenpatients with clinical stage T3a-4N0-1M0-1c consecutively treated with UHF-WPRT on a 1.5-T MR-Linac were recruited prospectively in a phase II trial (NCT05183074, ChiCTR2000033382). A 36.25 Gy dose in five fractions was delivered every other day with a boost of 40 Gy to the whole prostate, as well as 25 Gy to whole pelvic nodal area with a concomitant boost of 35 Gy to metastatic regional nodes. To estimate the delivered dose, we collected data by 3D-MR for the following stages: pre-MR, position verification-MR (PV-MR) in the Adapt-To-Shape (ATS) workflow, and 3D-MR during the beam-on phase (Bn-MR) and at the end of RT (post-MR). The target and organ-at-risk contours in the PV-MR, Bn-MR, and post-MR stages were projected from the pre-MR data by deformable image registration and manually adapted by the physician, followed by dose recalculation for the ATS plan. The cumulative acute genitourinary (GU) and gastrointestinal (GI) toxicities were evaluated as per NCI-CTCAE 5.0 criteria. The primary endpoints were acute ≥grade 3 genitourinary (GU) and gastrointestinal (GI) toxicities during the first 3 months.

RESULTS

Overall, 133 MR scans were collected (35 pre-MR, 35 PV-MR, 31 Bn-MR and 32 post-MR scans). With a median on-couch time of 61 minutes, the mean prostate and pelvic planning target volume (PTV)-V95% of all scans was 96.98 ± 3.06% and 96.44 ± 2.85%, respectively. The corresponding mean prostate clinical target volume (CTV)-V100% was 99.89 ± 0.32%, 98.71 ± 1.90%, 97.77 ± 2.89%, and 98.56 ± 1.72%, and the mean pelvic CTV-V100% was 97.57% ± 3.70%, 96.54 ± 3.80%, 95.43 ± 4.31%, and 94.39 ± 4.47% on pre-MR, PV-MR, Bn-MR and post-MR scans, respectively. For the 4 patients with positive nodes, the mean V100% of metastatic regional nodes was 99.89 ± 0.81%. The median V29 Gy change in the rectal wall was -1% (-18%-20%). The V29 Gy of the rectal wall increased by >15% was observed in one scan. A slight increase in the high dose of bladder wall was noted due to gradual bladder growth during the workflow. With median follow-up time of 7.3 (4.6-12.2) months, all patients were followed-up for more than 3 months. No patient was observed with acute CTCAE grade 2 or more severe GU or GI toxicities (0%).

CONCLUSION

UHF-RT to prostate and pelvic with ATS workflow is well tolerated by patients with HR and VHR prostate cancer, with only mild GU and GI toxicities. The 3D-MR-based dosimetry analysis demonstrated clinically acceptable estimated dose coverage of target volumes during the beam-on period.

Low-Dose Fractionated Radiotherapy Combined with Neoadjuvant Chemotherapy for T3-4 Nasopharyngeal Carcinoma Patients: The Preliminary Results of a Phase II Randomized Controlled Trial

PURPOSE/OBJECTIVE(S)

Over 70% of NPC patients were local advanced NPC (LANPC). The 5-year local recurrence-free survival rate is only 70% in T3-4 patients. Neoadjuvant chemotherapy (NACT) followed with concurrent chemoradiotherapy (CCRT) was recommended for LANPC patients. Low-dose fractionated radiotherapy (LDFRT), which is <100cGy, induces enhanced cell killing by the hyper-radiation sensitivity phenomenon and potentiates effects of chemotherapy. The synergy of LDFRT and NACT has not been used in the clinical practice and few studies focused on it. A single arm study found the ORR of primary site was improved to 90% for head and neck squamous carcinoma patients treated with LDFRT and NACT. Our previous study found the ORR of lymph nodes was higher in LDFRT group for high-risk LANPC patients. However, another study showed there was no significant difference between LDFRT and control group for LANPC patients. So, we aimed to investigate the potential efficacy of this novel neoadjuvant therapy for T3-4 NPC patients.

MATERIALS/METHODS

A total of 60 pathological confirmed T3-4 (UICC/AJCC8th) NPC patients were prospectively enrolled in our study. They were randomly assigned to two groups. For the LDFRT group, the patients received 3 cycles of NACT (docetaxel 75mg/m2 D1, cisplatin 80mg/m2 D1) with LDFRT, and followed with CCRT. LDFRT was delivered as 50cGy per fraction twice a day to primary site on D1,2 for each cycle of NACT. The patients in the control group only received NACT and followed with CCRT. All the patients underwent IGRT. RECIST criteria and CTCAE 5.0 was used to evaluate the ORR and toxicity at post-NACT and the completion of CCRT.

RESULTS

From February 2022 to December 2022, 60 T3-4 NPC patients were included, and 30 patients for each group. For the primary site, the median volume reduction rate and the ORR after NACT was significantly improved in LDFRT group (69.27% vs 40.10%, p<0.001;93.33% vs 73.33%, p = 0.038). For the median volume reduction rate of primary site and lymph node, it was also obviously improved in LDFRT group (86.59% vs 55.43%, p<0.001). Though there was a tendency of ORR improvement in LDFRT group, but no significant difference (96.67% vs 83.33%, p = 0.195). After the completion of CCRT, the median volume reduction rate of primary site had an increased tendency in LDFRT group (96.16% vs 88.3%, p = 0.065), but the ORR had no statistical significance (LDFRT group: CR 45.8%, PR 54.2%; control group: CR 37.5%, PR 62.5%). For the toxicity, the incidence of grade 3-4 adverse events had no difference between two groups (p = 0.786). No grade 5 adverse events occurred.

CONCLUSION

LDFRT combined with NACT could obviously improve the median volume reduction rate and ORR of primary tumor for T3-4 NPC patients, and the toxicity was similar and tolerable. This novel treatment could be a promising strategy to improve treatment response and needed to be confirmed further.

Long-Term Survival Outcome for Metastatic Nasopharyngeal Carcinoma Patients Receiving Radiation to Primary and Metastatic Sites with Palliative Chemotherapy

PURPOSE/OBJECTIVE(S)

A total of 6% - 8% of NPC patients were initial diagnosed as distant metastatic disease. The median overall survival (OS) is only 10-15 months with palliative chemotherapy for these patients. A phase III study showed that palliative chemotherapy combined with radical radiotherapy to primary site could be a newly effective treatment method for metastatic NPC. Another phase 2, RCT found that the patients who had the solid tumors with 1-5 metastases received standard palliative care plus stereotactic body radiation therapy (SABR), and the 5-year OS were improved to 42.3%. Nevertheless, there was few studies focus on the radiation to both primary site and metastatic lesions. Therefore, we aimed to investigate the potential clinical benefits for initial diagnosed metastatic NPC patients with radiation to both primary site and distant metastatic lesions plus palliative chemotherapy.

MATERIALS/METHODS

Metastatic NPC patients treated with radiation to both primary site and distant metastatic lesions plus palliative chemotherapy were retrospectively collected in our hospital from May 2008 to May 2022. For treatment group, all patients underwent IGRT according to ICRU reports 50 and 62. The prescribed dose for primary site: GTVT: ≥66Gy, GTVn: ≥66Gy, CTV1: 60-66Gy, CTV2 54-60Gy, CTVln 50-54Gy. And the prescribed dose for distant metastatic lesions was more than 30Gy. For the control group, the patients treated with palliative chemotherapy were selected by propensity score matching from our hospital. The regimen for palliative chemotherapy was cisplatin-based chemotherapy every three weeks (100mg/m2 D1) for both groups. Kaplan-Meier method was used to analyze the OS. Cox regression model was used for multivariate analysis.

RESULTS

A total of 54 metastatic NPC patients with radiation to both primary site and distant metastatic lesions were retrospectively included in the treatment group, and another 54 patients were selected as the control group. The median follow-up time was 52 months. In the treatment group, the median age was 52 years (37-82), male (68%), female (32%), the main metastatic sites were bone (36 cases, 66%), lung (18 cases, 33%) and liver (10 cases, 18%). There were 23 oligometastasis cases and 31 cases. 3-year and 5-year OS in the treatment group were both dramatically improved than control group (63.2% vs 50.6%, p<0.05; 49.6% vs 38.9%, p<0.05). Multivariate analysis showed that T stage, liver metastatic lesion and oligometastases were the independent prognostic factors for them.

CONCLUSION

Palliative chemotherapy combined with radiation to primary sites and distant metastatic lesions might improve the OS for initial diagnosed distant metastatic NPC patients. More prospective clinical trials were needed to confirm it further.

Cost-Effectiveness of Short-Course Radiotherapy Based Total Neoadjuvant Therapy for Locally Advanced Rectal Cancer in China

PURPOSE/OBJECTIVE(S)

The phase III STELLAR (NCT02533271) trial demonstrated that four cycles of chemotherapy after short-course radiotherapy (SCRT-TNT) were not inferior to the standard care of long-course concurrent radiotherapy (LCRT) in patients with locally advanced rectal cancer (LARC). This study assessed the cost-effectiveness of SCRT-TNT versus LCRT in locally advanced rectal cancer in China on the basis of the STELLAR trial.

MATERIALS/METHODS

A Markov model was used to synthesize the healthcare costs and benefits of LARC patients based on results from the STELLAR trial. The model assumes that LARC who meet the inclusion criteria of the STELLAR trial experience four possible states: No Evidence of Disease (NED), locally recurrence, distant metastases, or any death from rectal cancer or other unrelated causes, where local recurrence continues to be classified as resectable and unresectable. The transition status period is 3 month, and 5 years is used to calculate direct medical costs and health benefits. The probabilities of states transition after SCRT-TNT or LCRT were derived from the results of the STELLAR trial and previous published article (Table.1). Costs were evaluated from the Chinese payer's perspective reported in early 2022 US dollars (US$1 = 6.78 Chinese Yuan). Sensitivity analyses were performed for key variables. Cost-effectiveness was evaluated using the incremental cost-effectiveness ratio and net monetary benefits. Effectiveness was defined as quality-adjusted life-years (QALYs). Willingness-to-pay (WTP) threshold was set at $43500/QALY. Data were collected from October 3, 2020, to September 20, 2021, and analyzed from November 15, 2020, to October 25, 2021.

RESULTS

During the 5-year horizon, for the base case scenario, SCRT-TNT incurred a lower total cost and higher QALYs compared with LCCRT. The total cost was $65767 and QALYs were 1.77 for SCRT-TNT; for LCCRT, the total cost was $72802 and QALYs were 1.64. This resulted in an ICER of -$ 55470.69 per QALY. Therefore, SCRT-TNT was a cost-saving and dominating treatment strategy compared with LCRT. Sensitivity analysis showed that ICERs were most sensitive to the parameters of distant metastases risk after treatment.

CONCLUSION

SCRT-TNT in locally advanced rectal cancer can be a cost-effective alternative to LCRT in China, and should be considered in appropriately selected patients.

Feasibility of Universal Anomaly Detection without Knowing the Abnormality in Medical Images

Many anomaly detection approaches, especially deep learning methods, have been recently developed to identify abnormal image morphology by only employing normal images during training. Unfortunately, many prior anomaly detection methods were optimized for a specific "known" abnormality (e.g., brain tumor, bone fraction, cell types). Moreover, even though only the normal images were used in the training process, the abnormal images were often employed during the validation process (e.g., epoch selection, hyper-parameter tuning), which might leak the supposed "unknown" abnormality unintentionally. In this study, we investigated these two essential aspects regarding universal anomaly detection in medical images by (1) comparing various anomaly detection methods across four medical datasets, (2) investigating the inevitable but often neglected issues on how to unbiasedly select the optimal anomaly detection model during the validation phase using only normal images, and (3) proposing a simple decision-level ensemble method to leverage the advantage of different kinds of anomaly detection without knowing the abnormality. The results of our experiments indicate that none of the evaluated methods consistently achieved the best performance across all datasets. Our proposed method enhanced the robustness of performance in general (average AUC 0.956).

Lymphocyte Count Kinetics and the Effect of Different Radiotherapy Techniques on Radiation-Induced Lymphopenia in Patients with Breast Cancer Receiving Hypofractionated Postmastectomy Radiotherapy

PURPOSE/OBJECTIVE(S)

Radiation-induced lymphopenia (RIL) is associated with poor prognosis in solid tumors. This study aimed to describe the lymphocyte kinetics in patients with breast cancer receiving hypofractionated postmastectomy radiotherapy (RT) and to investigate the association of different RT techniques with RIL.

MATERIALS/METHODS

We assessed 607 patients who received hypofractionated postmastectomy RT for breast cancer in our prospective clinical database from 8 hospitals. All patients received irradiation to the chest wall and supraclavicular fossa. RT techniques included integrated RT with the photon-based intensity modulated techniques to irradiate all target volumes (integrated RT) and a hybrid approach combining photon irradiation to supraclavicular nodes and electron irradiation to the chest wall (hybrid RT). Peripheral lymphocyte counts (PLC) were tested prior to RT (baseline), weekly during RT, at 1, 2 weeks, 3, 6 months after RT, and then every 6 months. Grade 3+ RIL was defined as PLC nadir during RT of <0.5 ×103/ml. Mean PLC was compared by the t test. Univariate, multivariate, and propensity score matching (PSM) analyses were used to evaluate the effect of different RT techniques on grade 3+ RIL.

RESULTS

During RT, 121 (19.9%) of patients had grade 3+ RIL. The PLC started to recover at 1 week and reached baseline levels 1 year after RT. A greater proportion of the patients treated with the integrated RT (90/269, 33.5%) developed grade 3+ PLC compared with those receiving hybrid RT (31/338, 9.2%, P < 0.001). After conducting PSM, multivariate analyses showed lower baseline PLC (HR = 0.15, P<0.001) and RT technique (the integrated RT vs. hybrid RT, HR = 4.76, P<0.001) were independent risk factors for grade 3+ RIL. The PLC in patients receiving the integrated RT after RT were higher than that in those receiving hybrid RT (p<0.05).

CONCLUSION

RT technique affect the risk of and recovery from RIL, which may impact survival. Choosing appropriate RT technique to minimize RIL might be considered to benefit their outcomes.

[International comparison and assessment of the quality of drug clinical trial implementation in China based on scientific regulatory system]

With the rapid development of clinical research and the continuous enhancement of innovation capability in China, the quality of clinical research under China's scientific regulatory system has drawn widespread attention. This study evaluated the quality results of China's drug clinical trials implementation, compared the scientific regulatory systems of clinical research quality between China and the United States, analyzed real-world clinical application on the approval of new anti-tumor drugs through clinical trials, in order to analyze China's status and level of clinical trial implementation quality in the international industry, and explore the advantages and value of China's clinical research scientific regulation by collecting clinical trial data inspections disclosed by regulatory agencies in both China and the United States, as well as verifying information on the approval of new anti-tumor drugs.

Semantic-Aware Contrastive Learning for Multi-Object Medical Image Segmentation

Medical image segmentation, or computing voxel-wise semantic masks, is a fundamental yet challenging task in medical imaging domain. To increase the ability of encoder-decoder neural networks to perform this task across large clinical cohorts, contrastive learning provides an opportunity to stabilize model initialization and enhances downstream tasks performance without ground-truth voxel-wise labels. However, multiple target objects with different semantic meanings and contrast level may exist in a single image, which poses a problem for adapting traditional contrastive learning methods from prevalent "image-level classification" to "pixel-level segmentation". In this article, we propose a simple semantic-aware contrastive learning approach leveraging attention masks and image-wise labels to advance multi-object semantic segmentation. Briefly, we embed different semantic objects to different clusters rather than the traditional image-level embeddings. We evaluate our proposed method on a multi-organ medical image segmentation task with both in-house data and MICCAI Challenge 2015 BTCV datasets. Compared with current state-of-the-art training strategies, our proposed pipeline yields a substantial improvement of 5.53% and 6.09% on Dice score for both medical image segmentation cohorts respectively (p-value 0.01). The performance of the proposed method is further assessed on external medical image cohort via MICCAI Challenge FLARE 2021 dataset, and achieves a substantial improvement from Dice 0.922 to 0.933 (p-value 0.01).

Bacteria-based immunotherapy for cancer: a systematic review of preclinical studies

Immunotherapy has been emerging as a powerful strategy for cancer management. Recently, accumulating evidence has demonstrated that bacteria-based immunotherapy including naive bacteria, bacterial components, and bacterial derivatives, can modulate immune response via various cellular and molecular pathways. The key mechanisms of bacterial antitumor immunity include inducing immune cells to kill tumor cells directly or reverse the immunosuppressive microenvironment. Currently, bacterial antigens synthesized as vaccine candidates by bioengineering technology are novel antitumor immunotherapy. Especially the combination therapy of bacterial vaccine with conventional therapies may further achieve enhanced therapeutic benefits against cancers. However, the clinical translation of bacteria-based immunotherapy is limited for biosafety concerns and non-uniform production standards. In this review, we aim to summarize immunotherapy strategies based on advanced bacterial therapeutics and discuss their potential for cancer management, we will also propose approaches for optimizing bacteria-based immunotherapy for facilitating clinical translation.

Automatic Visual Acuity Loss Prediction in Children with Optic Pathway Gliomas using Magnetic Resonance Imaging

Children with optic pathway gliomas (OPGs), a low-grade brain tumor associated with neurofibromatosis type 1 (NF1-OPG), are at risk for permanent vision loss. While OPG size has been associated with vision loss, it is unclear how changes in size, shape, and imaging features of OPGs are associated with the likelihood of vision loss. This paper presents a fully automatic framework for accurate prediction of visual acuity loss using multi-sequence magnetic resonance images (MRIs). Our proposed framework includes a transformer-based segmentation network using transfer learning, statistical analysis of radiomic features, and a machine learning method for predicting vision loss. Our segmentation network was evaluated on multi-sequence MRIs acquired from 75 pediatric subjects with NF1-OPG and obtained an average Dice similarity coefficient of 0.791. The ability to predict vision loss was evaluated on a subset of 25 subjects with ground truth using cross-validation and achieved an average accuracy of 0.8. Analyzing multiple MRI features appear to be good indicators of vision loss, potentially permitting early treatment decisions.Clinical relevance- Accurately determining which children with NF1-OPGs are at risk and hence require preventive treatment before vision loss remains challenging, towards this we present a fully automatic deep learning-based framework for vision outcome prediction, potentially permitting early treatment decisions.

[Identification and verification of α-11 giardin-interacting protein]

OBJECTIVE

To identify and verify the interacting protein of α-11 giardin, so as provide the experimental evidence for studies on the α-11 giardin function.

METHODS

The yeast two-hybrid cDNA library of the Giardia lambia C2 strain and the bait plasmid of α-11 giardin were constructed. All proteins interacting with α-11 giardin were screened using the yeast two-hybrid system. α-11 giardin and all screened potential interacting protein genes were constructed into pBiFc-Vc-155 and pBiFc-Vn-173 plasmids, and co-transfected into the breast cancer cell line MDA-MB-231. The interactions between α-11 giardin and interacting proteins were verified using bimolecular fluorescence complementation (BiFC).

RESULTS

The yeast two-hybrid G. lambia cDNA library which was quantified at 2.715 × 10⁷ colony-forming units (CFU) and the bait plasmid containing α-11 giardin gene without an autoactivation activity were constructed. Following two-round positive screening with the yeast two-hybrid system, two potential proteins interacting with α-11 giardin were screened, including eukaryotic translation initiation factor 5A (EIF5A), calmodulin-dependent protein kinase (CAMKL) and nicotinamide adenine dinucleotide phosphate-specific glutamate dehydrogenase (NADP-GDH), hypothetical protein 1 (GL50803_95880), hypothetical protein 2 (GL50803_87261) and a protein from Giardia canis virus. The α-11 giardin and EIF5A genes were transfected into the pBiFc-Vc-155 and pBiFc-Vn-173 plasmids using BiFC, and the recombinant plasmids pBiFc-Vc-155-α-11 and pBiFc-Vn-173-EIF5A were co-tranfected into MDA-MB-231 cells, which displayed green fluorescence under a microscope, indicating the interaction between α-11 giardin and EIF5A protein in cells.

CONCLUSIONS

The yeast two-hybrid cDNA library of the G. lambia C2 strain has been successfully constructed, and six potential protein interacting with α-11 giardin have been identified, including EIF5A that interacts with α-11 giardin in cells.

PI3K Inhibition Restores and Amplifies Response to Ruxolitinib in patients with Myelofibrosis

PURPOSE

Treatment options are limited beyond JAK inhibitors for patients with primary myelofibrosis (PMF), or secondary MF. Preclinical studies have revealed that PI3Kδ inhibition cooperates with ruxolitinib, a JAK1/2 inhibitor, to reduce proliferation and induce apoptosis of JAK2V617F mutant cell lines.

PATIENTS AND METHODS

In a phase I dose-escalation and expansion study, we evaluated the safety and efficacy of a selective PI3Kδ inhibitor umbralisib in combination with ruxolitinib in MF patients who had a suboptimal response or lost response to ruxolitinib. Enrolled subjects were required to be on a stable dose of ruxolitinib for ≥8 weeks and continue that maximally tolerated dose at study enrollment. The recommended dose of umbralisib in combination with ruxolitinib was determined using a modified 3+3 dose escalation design. Safety, pharmacokinetics, and efficacy outcomes were evaluated, and spleen size was measured with a novel automated digital atlas.

RESULTS

Thirty-seven MF patients with prior exposure to ruxolitinib were enrolled. 2 patients treated with 800mg umbralisib experienced reversible Grade 3 asymptomatic pancreatic enzyme elevation, but no dose-limiting toxicities were seen at lower umbralisib doses. Two patients (5%) achieved complete response (CR), and 12 patients (32%) met the IWG-MRT response criteria of clinical improvement (CI). With a median follow-up of 50.3 months for censored patients, overall survival was greater than 70% after 3 years of follow-up.

CONCLUSIONS

Adding umbralisib to ruxolitinib in patients was well-tolerated and may re-sensitize MF patients to ruxolitinib without unacceptable rates of adverse events seen with earlier generation PI3Kδ inhibitors.

Causal relationship between Type 1 diabetes and osteoporosis and fracture occurrence: a two-sample Mendelian randomization analysis

We used two-sample Mendelian Randomization to reveal causal estimates of type 1 diabetes and bone. Type 1 diabetes was found to be a risk factor for bone metabolic health, although there was no clear evidence to support a genetic association between type 1 diabetes and osteoporosis and fracture risk.

INTRODUCTION

Based on the random assignment of gametes at conception, Mendelian randomization (MR) analysis simulates randomized controlled trials in an observational setting. Therefore, we used MR to assess the association causality of type 1 diabetes (T1D) with fractures and osteoporosis.

METHODS

From a genome-wide association meta-analysis, independent single nucleotide polymorphisms closely associated with T1D were selected as instrumental variables. Data on fracture and osteoporosis were obtained from the FinnGen Consortium. We performed a two-sample MR analysis, using inverse-variance weighted (IVW) as the primary analysis method, to assess possible causal associations between T1D and bone risk. The results were verified by MR-Egger regression and median weighted method (WME). MR-PRESSO and MR-Egger intercepts were used to evaluate the horizontal pleiotropy of instrumental variables, and the Q-test and "leave-one-out" methods were used to test the heterogeneity of MR results.

RESULTS

IVW (OR=1.040, 95% CI=0.974-1.109, P=0.238), MR-Egger regression (OR=1.077, 95% CI=0.921-1.260, P=0.372) and WME (OR=1.021, 95% CI=0.935-1.114, P=0.643) all showed that there was no causal relationship between T1D and osteoporosis, but the direction was consistent. The indicative significance of IVW results in T1D and forearm fractures (OR=1.062, 95% CI=1.010-1.117, P=0.020), but the results are not robust enough. There was no causal effect in femur, lumbar and pelvis, or shoulder and upper arm fractures.

CONCLUSIONS

After MR analysis, although T1D may be a risk factor for bone health, we do not have sufficient evidence to support a causal effect of T1D on osteoporosis and fractures at a genetically predicted level. More cases need to be included for analysis.

Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives

Transformer, one of the latest technological advances of deep learning, has gained prevalence in natural language processing or computer vision. Since medical imaging bear some resemblance to computer vision, it is natural to inquire about the status quo of Transformers in medical imaging and ask the question: can the Transformer models transform medical imaging? In this paper, we attempt to make a response to the inquiry. After a brief introduction of the fundamentals of Transformers, especially in comparison with convolutional neural networks (CNNs), and highlighting key defining properties that characterize the Transformers, we offer a comprehensive review of the state-of-the-art Transformer-based approaches for medical imaging and exhibit current research progresses made in the areas of medical image segmentation, recognition, detection, registration, reconstruction, enhancement, etc. In particular, what distinguishes our review lies in its organization based on the Transformer's key defining properties, which are mostly derived from comparing the Transformer and CNN, and its type of architecture, which specifies the manner in which the Transformer and CNN are combined, all helping the readers to best understand the rationale behind the reviewed approaches. We conclude with discussions of future perspectives.

[Micro-CT analysis of tooth development of C57BL/6 mice strain]

Objective: To investigate the normal process of tooth development of C57BL/6 mouse strain by using micro-CT for better understanding about the tooth development of the human being and other species. Methods: A total of 54 C57BL/6 mice were used at postnatal day 1 (P1), P3, P7, P10, P14, P21, P28, P42 and P56 (n=6 for each age group). After euthanasia, the skulls and alveolar bones (with molars) were isolated and scanned by micro-CT scanner. After three dimensional reconstruction, the developmental status of the crown and root(s) for each tooth type was examined in different views. Results: The tooth development of mice from birth to mature (P56) could be divided into three stages. The first stage was from P1 to P14, in which the crowns of all the first, second and third molars had formed, while the roots had not fully developed yet. The second stage was from ablactation (P21) to P28, in which all the roots of the molars had reached their normal length, and the apical foramens had closed. Due to the mastication and occlusal abrasion, the incisors exhibited sharp cutting edges at the buccal enamel layer, and the corresponding molars formed a pit-to-fossa articulated relationship. The third stage was from P42 to P56, in which the root canal differentiation occurred, and 1-2 canal configuration was formed in several flat roots. The development of molar roots had completed and the apexes were enlarged due to the deposition of cementum around. Conclusions: In the process of mouse tooth development, the mineralization of the cusps, followed by crown formation and roots elongation, was precisely regulated in a spatial-temporal pattern. The incisors and the molars exhibited different modes of development.

[Survival analysis of patients with intrahepatic cholangiocarcinoma treated with adjuvant chemotherapy after radical resection based on CoxPH model and deep learning algorithm]

Objective: To establish a predictive model for survival benefit of patients with intrahepatic cholangiocarcinoma (ICC) who received adjuvant chemotherapy after radical resection. Methods: The clinical and pathological data of 249 patients with ICC who underwent radical resection and adjuvant chemotherapy at 8 hospitals in China from January 2010 to December 2018 were retrospectively collected. There were 121 males and 128 females,with 88 cases>60 years old and 161 cases≤60 years old. Feature selection was performed by univariate and multivariate Cox regression analysis. Overall survival time and survival status were used as outcome indicators,then target clinical features were selected. Patients were stratified into high-risk group and low-risk group,survival differences between the two groups were analyzed. Using the selected clinical features, the traditional CoxPH model and deep learning DeepSurv survival prediction model were constructed, and the performance of the models were evaluated according to concordance index(C-index). Results: Portal vein invasion, carcinoembryonic antigen>5 μg/L,abnormal lymphocyte count, low grade tumor pathological differentiation and positive lymph nodes>0 were independent adverse prognostic factors for overall survival in 249 patients with adjuvant chemotherapy after radical resection (all P<0.05). The survival benefit of adjuvant chemotherapy in the high-risk group was significantly lower than that in the low-risk group (P<0.05). Using the above five features, the traditional CoxPH model and the deep learning DeepSurv survival prediction model were constructed. The C-index values of the training set were 0.687 and 0.770, and the C-index values of the test set were 0.606 and 0.763,respectively. Conclusion: Compared with the traditional Cox model, the DeepSurv model can more accurately predict the survival probability of patients with ICC undergoing adjuvant chemotherapy at a certain time point, and more accurately judge the survival benefit of adjuvant chemotherapy.

[The efficacy of radiotherapy based combined therapy for unresectable locally invasive bladder cancer and its associated factors analysis]

Objective: Retrospective analysis of the efficacy and influencing factors of bladder preservation integrated therapy for unresectable invasive bladder cancer confined to the pelvis was done, also including the bladder function preservation and adverse effects analysis. Methods: Sixty-nine patients with unresectable locally invasive bladder cancer who received radiotherapy-based combination therapy from March 1999 to December 2021 at our hospital were selected. Among them, 42 patients received concurrent chemoradiotherapy, 32 underwent neoadjuvant chemotherapyand 43 with transurethral resection of bladder tumors (TURBT) prior to radiotherapy. The late adverse effect of radiotherapy, preservation of bladder function, replase and metastasis and survival were followed-up. Cox proportional hazards models were applied for the multifactorial analysis. Results: The median age was 69 years. There were 63 cases (91.3%) of uroepithelial carcinoma, 64 of stage Ⅲ and 4 of stage Ⅳ. The median duration of follow-up was 76 months. There were 7 grade 2 late genito urinary toxicities, 2 grade 2 gastrointestinal toxicities, no grade 3 or higher adverse events occurred. All patients maintained normal bladder function, except for 8 cases who lost bladder function due to uncontrolled tumor in the bladder. Seventeen cases recurred locally. There were 11 cases in the concurrent chemoradiotherapy group with a local recurrence rate of 26.2% (11/42) and 6 cases in the non-concurrent chemoradiotherapy group with a local recurrence rate of 22.2% (6/27), and the difference in local recurrence rate between the two groups was not statistically significant (P=0.709). There were 23 cases of distant metastasis (including 2 cases of local recurrence with distant metastasis), including 10 cases in the concurrent chemoradiotherapy group with a distant metastasis rate of 23.8% (10/42) and 13 cases in the non-concurrent chemoradiotherapy group with a distant metastasis rate of 48.1% (13/27), and the distant metastasis rate in the non-concurrent chemoradiotherapy group was higher than that in the concurrent chemoradiotherapy group (P=0.036). The median 5-year overall survival (OS) time was 59 months and the OS rate was 47.8%. The 5-year progression-free survival (PFS) time was 20 months and the PFS rate was 34.4%. The 5-year OS rates of concurrent and non-concurrent chemoradiotherapy group were 62.9% and 27.6% (P<0.001), and 5-year PFS rates were 45.4% and 20.0%, respectively (P=0.022). The 5-year OS rates of with or without neoadjuvant chemotherapy were 78.4% and 30.1% (P=0.002), and the 5-year PFS rates were 49.1% and 25.1% (P=0.087), respectively. The 5-year OS rates with or without TURBT before radiotherapy were 45.5% and 51.9% (P=0.233) and the 5-year PFS rates were 30.8% and 39.9% (P=0.198), respectively. Multivariate Cox regression analysis results showed that the clinical stage (HR=0.422, 95% CI: 0.205-0.869) was independent prognostic factor for PFS of invasive bladder cancer. The multivariate analysis showed that clinical stages (HR=0.278, 95% CI: 0.114-0.678), concurrent chemoradiotherapy (HR=0.391, 95% CI: 0.165-0.930), neoadjuvant chemotherapy (HR=0.188, 95% CI: 0.058-0.611), and recurrences (HR=10.855, 95% CI: 3.655-32.638) were independent prognostic factors for OS of invasive bladder cancer. Conclusion: Unresectable localized invasive bladder cancer can achieve satisfactory long-term outcomes with bladder-preserving combination therapy based on radiotherapy, most patients can retain normal bladder function with acceptable late adverse effects and improved survival particularly evident in patients with early, concurrent chemoradiotherapy and neoadjuvant chemotherapy.

[A nomogram for preoperative prediction of lymph node metastasis in patients with intrahepatic cholangiocarcinoma based on inflammation-related markers]

Objectives: To construct a nomogram for prediction of intrahepatic cholangiocarcinoma (ICC) lymph node metastasis based on inflammation-related markers,and to conduct its clinical verification. Methods: Clinical and pathological data of 858 ICC patients who underwent radical resection were retrospectively collected at 10 domestic tertiary hospitals in China from January 2010 to December 2018. Among the 508 patients who underwent lymph node dissection,207 cases had complete variable clinical data for constructing the nomogram,including 84 males,123 females,109 patients≥60 years old,98 patients<60 years old and 69 patients were pathologically diagnosed with positive lymph nodes after surgery. Receiver operating characteristic curve was drawn to calculate the accuracy of preoperative imaging examinations to determine lymph node status,and the difference in overall survival time was compared by Log-rank test. Partial regression squares and statistically significant preoperative variables were screened by backward stepwise regression analysis. R software was applied to construct a nomogram,clinical decision curve and clinical influence curve,and Bootstrap method was used for internal verification. Moreover,retrospectively collecting clinical information of 107 ICC patients with intraoperative lymph node dissection admitted to 9 tertiary hospitals in China from January 2019 to June 2021 was for external verification to verify the accuracy of the nomogram. 80 patients with complete clinical data but without lymph node dissection were divided into lymph node metastasis high-risk group and low-risk group according to the score of the nomogram among the 858 patients. Log-rank test was used to compare the overall survival of patients with or without lymph node metastasis diagnosed by pathology. Results: The area under the curve of preoperative imaging examinations for lymph node status assessment of 440 patients was 0.615,with a false negative rate of 62.8% (113/180) and a false positive rate of 14.2% (37/260). The median survival time of 207 patients used to construct a nomogram with positive or negative postoperative pathological lymph node metastases was 18.5 months and 27.1 months,respectively (P<0.05). Five variables related to lymph node metastasis were screened out by backward stepwise regression analysis,which were combined calculi,neutrophil/lymphocyte ratio,albumin,liver capsule invasion and systemic immune inflammation index,according to which a nomogram was constructed with concordance index(C-index) of 0.737 (95%CI: 0.667 to 0.806). The C-index of external verification was 0.674 (95%CI:0.569 to 0.779). The calibration prediction curve was in good agreement with the reference curve. The results of the clinical decision curve showed that when the risk threshold of high lymph node metastasis in the nomogram was set to about 0.32,the maximum net benefit could be obtained by 0.11,and the cost/benefit ratio was 1∶2. The results of clinical influence curve showed that when the risk threshold of high lymph node metastasis in the nomogram was set to about 0.6,the probability of correctly predicting lymph node metastasis could reach more than 90%. There was no significant difference in overall survival time between patients with high/low risk of lymph node metastasis assessed by the nomogram and those with pathologically confirmed lymph node metastasis or without lymph node metastasis (Log-rank test:P=0.082 and 0.510,respectively). Conclusion: The prediction accuracy of preoperative nomogram for ICC lymph node metastasis based on inflammation-related markers is satisfactory,which can be used as a supplementary method for preoperative diagnosis of lymph node metastasis and is helpful for clinicians to make personalized decision of lymph node dissection for patients with ICC.

[Exploring the significance of chemotherapy in the perioperative application of biliary tract carcinomas]

Biliary tract cancer is extremely malignant with a poor prognosis. At the moment, the only curative method available is radical resection. Targeted and immunotherapy are currently advancing quickly, but chemotherapy still holds a key role in the perioperative management of biliary cancer. Perioperative chemotherapy aims to decrease tumor volume before surgery so that patients can have their tumors surgically removed or have a higher radical resection rate. It also aims to remove any tumor cells that remain after surgery and prevent the growth of new tumors. Chemotherapy-based combination treatment techniques have been increasingly investigated in recent years to improve perioperative care and patient survival. From the standpoint of chemotherapy regimens and clinical trial success in the perioperative phase of radical surgery, the value of chemotherapy in the perioperative period of biliary tract cancer were explored in this paper.

Time-distance vision transformers in lung cancer diagnosis from longitudinal computed tomography

Features learned from single radiologic images are unable to provide information about whether and how much a lesion may be changing over time. Time-dependent features computed from repeated images can capture those changes and help identify malignant lesions by their temporal behavior. However, longitudinal medical imaging presents the unique challenge of sparse, irregular time intervals in data acquisition. While self-attention has been shown to be a versatile and efficient learning mechanism for time series and natural images, its potential for interpreting temporal distance between sparse, irregularly sampled spatial features has not been explored. In this work, we propose two interpretations of a time-distance vision transformer (ViT) by using (1) vector embeddings of continuous time and (2) a temporal emphasis model to scale self-attention weights. The two algorithms are evaluated based on benign versus malignant lung cancer discrimination of synthetic pulmonary nodules and lung screening computed tomography studies from the National Lung Screening Trial (NLST). Experiments evaluating the time-distance ViTs on synthetic nodules show a fundamental improvement in classifying irregularly sampled longitudinal images when compared to standard ViTs. In cross-validation on screening chest CTs from the NLST, our methods (0.785 and 0.786 AUC respectively) significantly outperform a cross-sectional approach (0.734 AUC) and match the discriminative performance of the leading longitudinal medical imaging algorithm (0.779 AUC) on benign versus malignant classification. This work represents the first self-attention-based framework for classifying longitudinal medical images. Our code is available at https://github.com/tom1193/time-distance-transformer.

Batch size: go big or go home? Counterintuitive improvement in medical autoencoders with smaller batch size

Batch size is a key hyperparameter in training deep learning models. Conventional wisdom suggests larger batches produce improved model performance. Here we present evidence to the contrary, particularly when using autoencoders to derive meaningful latent spaces from data with spatially global similarities and local differences, such as electronic health records (EHR) and medical imaging. We investigate batch size effects in both EHR data from the Baltimore Longitudinal Study of Aging and medical imaging data from the multimodal brain tumor segmentation (BraTS) challenge. We train fully connected and convolutional autoencoders to compress the EHR and imaging input spaces, respectively, into 32-dimensional latent spaces via reconstruction losses for various batch sizes between 1 and 100. Under the same hyperparameter configurations, smaller batches improve loss performance for both datasets. Additionally, latent spaces derived by autoencoders with smaller batches capture more biologically meaningful information. Qualitatively, we visualize 2-dimensional projections of the latent spaces and find that with smaller batches the EHR network better separates the sex of the individuals, and the imaging network better captures the right-left laterality of tumors. Quantitatively, the analogous sex classification and laterality regressions using the latent spaces demonstrate statistically significant improvements in performance at smaller batch sizes. Finally, we find improved individual variation locally in visualizations of representative data reconstructions at lower batch sizes. Taken together, these results suggest that smaller batch sizes should be considered when designing autoencoders to extract meaningful latent spaces among EHR and medical imaging data driven by global similarities and local variation.

Deep whole brain segmentation of 7T structural MRI

7T magnetic resonance imaging (MRI) has the potential to drive our understanding of human brain function through new contrast and enhanced resolution. Whole brain segmentation is a key neuroimaging technique that allows for region-by-region analysis of the brain. Segmentation is also an important preliminary step that provides spatial and volumetric information for running other neuroimaging pipelines. Spatially localized atlas network tiles (SLANT) is a popular 3D convolutional neural network (CNN) tool that breaks the whole brain segmentation task into localized sub-tasks. Each sub-task involves a specific spatial location handled by an independent 3D convolutional network to provide high resolution whole brain segmentation results. SLANT has been widely used to generate whole brain segmentations from structural scans acquired on 3T MRI. However, the use of SLANT for whole brain segmentation from structural 7T MRI scans has not been successful due to the inhomogeneous image contrast usually seen across the brain in 7T MRI. For instance, we demonstrate the mean percent difference of SLANT label volumes between a 3T scan-rescan is approximately 1.73%, whereas its 3T-7T scan-rescan counterpart has higher differences around 15.13%. Our approach to address this problem is to register the whole brain segmentation performed on 3T MRI to 7T MRI and use this information to finetune SLANT for structural 7T MRI. With the finetuned SLANT pipeline, we observe a lower mean relative difference in the label volumes of ~8.43% acquired from structural 7T MRI data. Dice similarity coefficient between SLANT segmentation on the 3T MRI scan and the after finetuning SLANT segmentation on the 7T MRI increased from 0.79 to 0.83 with p<0.01. These results suggest finetuning of SLANT is a viable solution for improving whole brain segmentation on high resolution 7T structural imaging.

Topological-Preserving Membrane Skeleton Segmentation in Multiplex Immunofluorescence Imaging

Multiplex immunofluorescence (MxIF) is an emerging imaging technology whose downstream molecular analytics highly rely upon the effectiveness of cell segmentation. In practice, multiple membrane markers (e.g., NaKATPase, PanCK and β-catenin) are employed to stain membranes for different cell types, so as to achieve a more comprehensive cell segmentation since no single marker fits all cell types. However, prevalent watershed-based image processing might yield inferior capability for modeling complicated relationships between markers. For example, some markers can be misleading due to questionable stain quality. In this paper, we propose a deep learning based membrane segmentation method to aggregate complementary information that is uniquely provided by large scale MxIF markers. We aim to segment tubular membrane structure in MxIF data using global (membrane markers z-stack projection image) and local (separate individual markers) information to maximize topology preservation with deep learning. Specifically, we investigate the feasibility of four SOTA 2D deep networks and four volumetric-based loss functions. We conducted a comprehensive ablation study to assess the sensitivity of the proposed method with various combinations of input channels. Beyond using adjusted rand index (ARI) as the evaluation metric, which was inspired by the clDice, we propose a novel volumetric metric that is specific for skeletal structure, denoted as c l D i c e S K E L . In total, 80 membrane MxIF images were manually traced for 5-fold cross-validation. Our model outperforms the baseline with a 20.2% and 41.3% increase in c l D i c e S K E L and ARI performance, which is significant (p<0.05) using the Wilcoxon signed rank test. Our work explores a promising direction for advancing MxIF imaging cell segmentation with deep learning membrane segmentation. Tools are available at https://github.com/MASILab/MxIF_Membrane_Segmentation.

Longitudinal Variability Analysis on Low-dose Abdominal CT with Deep Learning-based Segmentation

Metabolic health is increasingly implicated as a risk factor across conditions from cardiology to neurology, and efficiency assessment of body composition is critical to quantitatively characterizing these relationships. 2D low dose single slice computed tomography (CT) provides a high resolution, quantitative tissue map, albeit with a limited field of view. Although numerous potential analyses have been proposed in quantifying image context, there has been no comprehensive study for low-dose single slice CT longitudinal variability with automated segmentation. We studied a total of 1816 slices from 1469 subjects of Baltimore Longitudinal Study on Aging (BLSA) abdominal dataset using supervised deep learning-based segmentation and unsupervised clustering method. 300 out of 1469 subjects that have two year gap in their first two scans were pick out to evaluate longitudinal variability with measurements including intraclass correlation coefficient (ICC) and coefficient of variation (CV) in terms of tissues/organs size and mean intensity. We showed that our segmentation methods are stable in longitudinal settings with Dice ranged from 0.821 to 0.962 for thirteen target abdominal tissues structures. We observed high variability in most organ with ICC<0.5, low variability in the area of muscle, abdominal wall, fat and body mask with average ICC≥0.8. We found that the variability in organ is highly related to the cross-sectional position of the 2D slice. Our efforts pave quantitative exploration and quality control to reduce uncertainties in longitudinal analysis.

Unsupervised Registration Refinement for Generating Unbiased Eye Atlas

With the confounding effects of demographics across large-scale imaging surveys, substantial variation is demonstrated with the volumetric structure of orbit and eye anthropometry. Such variability increases the level of difficulty to localize the anatomical features of the eye organs for populational analysis. To adapt the variability of eye organs with stable registration transfer, we propose an unbiased eye atlas template followed by a hierarchical coarse-to-fine approach to provide generalized eye organ context across populations. Furthermore, we retrieved volumetric scans from 1842 healthy patients for generating an eye atlas template with minimal biases. Briefly, we select 20 subject scans and use an iterative approach to generate an initial unbiased template. We then perform metric-based registration to the remaining samples with the unbiased template and generate coarse registered outputs. The coarse registered outputs are further leveraged to train a deep probabilistic network, which aims to refine the organ deformation in unsupervised setting. Computed tomography (CT) scans of 100 de-identified subjects are used to generate and evaluate the unbiased atlas template with the hierarchical pipeline. The refined registration shows the stable transfer of the eye organs, which were well-localized in the high-resolution (0.5 mm³) atlas space and demonstrated a significant improvement of 2.37% Dice for inverse label transfer performance. The subject-wise qualitative representations with surface rendering successfully demonstrate the transfer details of the organ context and showed the applicability of generalizing the morphological variation across patients.

Associations of Pain and Sarcopenia with Successful Aging among Older People in China: Evidence from CHARLS

OBJECTIVES

Sarcopenia and chronic pain are geriatric syndromes that negatively impact the lives of older people. The aim of this study was to explore the relationship among sarcopenia, pain, and successful aging among older persons participating in the China Health and Retirement Longitudinal Study (CHARLS).

DESIGN

Cohort study with a 2-year follow-up.

SETTING AND PARTICIPANTS

Data were derived from 2 waves of the CHARLS, and 4280 community-dwelling participants aged ≥ 60 years were included in the study.

METHODS

Sarcopenia status was defined according to the Asian Working Group for Sarcopenia 2019 (AWGS 2019) criteria. Successful aging was defined following Rowe and Kahn's multidimensional model. Pain was assessed by a self-reported questionnaire. A generalized estimating equation (GEE) was used to examine the associations.

RESULTS

Longitudinal results demonstrated that compared with no sarcopenia, possible sarcopenia [OR (95%CI): 0.600 (0.304~1.188)] was not significantly associated with successful aging. Pain only was strongly associated with successful aging [0.388 (0.251~0.600)], whereas the association between sarcopenia only and successful aging was weaker [0.509 (0.287~0.905)]. The likelihood of being successful aging was substantially lower in the presence of coexisting sarcopenia and pain [0.268 (0.108~0.759)].

CONCLUSIONS

Both pain and sarcopenia are significant predictors for achieving successful aging among community-dwelling older adults. Early identification of sarcopenia and pain permits the implementation of treatment strategies and presents an opportunity to mitigate the risk of being unsuccessful aging.

The Therapeutic and Prognostic Role of Clusterin in Diverse Musculoskeletal Diseases: A Mini Review

This mini-review aims to introduce the association between Secretory clusterin/apolipoprotein J (sCLU) and diverse musculoskeletal diseases. A comprehensive review of the literature was performed to identify basic science and clinical studies, which implied the therapeutic and prognostic role of sCLU in diverse musculoskeletal diseases. sCLU is a multifunctional glycoprotein that is ubiquitously expressed in various tissues and is implicated in many pathophysiological processes. Dysregulated expression of sCLU had been reported to be assocaited with proliferative or apoptotic molecular processes and inflammatory responses, which participated in many pathophysiological processes such as degenerative musculoskeletal diseases including ischemic osteonecrosis, osteoarthritis (OA) and degenerative cervical myelopathy (spinal cord injury), neoplastic musculoskeletal diseases, inflammatory and autoimmune musculoskeletal diseases including Rheumatoid arthritis (RA), joint damage induced by Brucella abortus, Sjogren's syndrome, idiopathic inflammatory myopathies, muscle glucose metabolism, insulin sensitivity and traumatic musculoskeletal diseases. Recent findings of sCLU in these musculoskeletal diseases provides insights on the therapeutic and prognostic role of sCLU in these musculoskeletal diseases. sCLU may serve as a promising therapeutic target for ischemic osteonecrosis, OA and spinal cord injury as well as a potential prognostic biomarker for OA and RA. Moreover, sCLU could act as a prognostic biomarker for osteosarcoma (OS) and a promising therapeutic target for OS resistance. Although many studies support the potential therapeutic and prognostic role of sCLU in some inflammatory and autoimmune-mediated musculoskeletal diseases, more future researches are needed to explore the molecular pathogenic mechanism mediated by sCLU implied in these musculoskeletal diseases.

Rh‐endostatin plus camrelizumab and chemotherapy in first‐line treatment of advanced non‐small cell lung cancer: A multicenter retrospective study

BACKGROUND

Clinical evidence of immune checkpoint inhibitors combined with antiangiogenic drugs in patients with advanced non-small cell lung cancer (NSCLC) was limited. Recombinant human endostatin (rh-endostatin), an antiangiogenic drug, and camrelizumab, an anti-PD-1 antibody, have been approved for the treatment of advanced NSCLC in China. This study aimed to investigate the efficacy and safety of rh-endostatin plus camrelizumab and chemotherapy in the treatment of advanced NSCLC.

METHODS

Eligible patients were enrolled and received camrelizumab (200 mg, day 1) every 3 weeks and continuous intravenous infusion of rh-endostatin (70 mg/day, days 1-3) and cisplatin combined with pemetrexed (for adenocarcinoma) or paclitaxel (for NSCLC other than adenocarcinoma) every 3 weeks. Primary endpoint was progression-free survival (PFS). Secondary endpoints were objective response rate (ORR), disease control rate (DCR), overall survival (OS), and safety profiles.

RESULTS

Overall, 27 patients were included, and 25 patients were eligible for efficacy evaluation. For these 25 patients, ORR was 48.15% (13/27) and DCR was 85.19% (23/27). With a median follow-up of 10.37 months, the median PFS was 8.9 (95% CI: 4.23-13.57) months. Median OS was not reached. Overall, 96.3% of patients experienced at least one treatment-related adverse event, and grade 3 TRAEs occurred in 9 (33.3%) patients. No unexpected AEs were observed.

CONCLUSION

Rh-endostatin plus camrelizumab and chemotherapy showed favorable efficacy and safety profile in patients with advanced NSCLC, representing a promising treatment regimen for these patients.

Nomogram Based on Clinical and Radiomics Data for Predicting Radiation-induced Temporal Lobe Injury in Patients with Non-metastatic Stage T4 Nasopharyngeal Carcinoma

AIMS

To use pre-treatment magnetic resonance imaging-based radiomics data with clinical data to predict radiation-induced temporal lobe injury (RTLI) in nasopharyngeal carcinoma (NPC) patients with stage T4/N0-3/M0 within 5 years after radiotherapy.

MATERIALS AND METHODS

This study retrospectively examined 98 patients (198 temporal lobes) with stage T4/N0-3/M0 NPC. Participants were enrolled into a training cohort or a validation cohort in a ratio of 7:3. Radiomics features were extracted from pre-treatment magnetic resonance imaging that were T1-and T2-weighted. Spearman rank correlation, the t-test and the least absolute shrinkage and selection operator (LASSO) algorithm were used to select significant radiomics features; machine-learning models were used to generate radiomics signatures (Rad-Scores). Rad-Scores and clinical factors were integrated into a nomogram for prediction of RTLI. Nomogram discrimination was evaluated using receiver operating characteristic analysis and clinical benefits were evaluated using decision curve analysis.

RESULTS

Participants were enrolled into a training cohort (n = 139) or a validation cohort (n = 59). In total, 3568 radiomics features were initially extracted from T1-and T2-weighted images. Age, D_max, D_1cc and 16 stable radiomics features (six from T1-weighted and 10 from T2-weighted images) were identified as independent predictive factors. A greater Rad-Score was associated with a greater risk of RTLI. The nomogram showed good discrimination, with a C-index of 0.85 (95% confidence interval 0.79-0.92) in the training cohort and 0.82 (95% confidence interval 0.71-0.92) in the validation cohort.

CONCLUSION

We developed models for the prediction of RTLI in patients with stage T4/N0-3/M0 NPC using pre-treatment radiomics data and clinical data. Nomograms from these pre-treatment data improved the prediction of RTLI. These results may allow the selection of patients for earlier clinical interventions.