Enhancing acute stroke assessment: evaluating the clinical utility of the "Real" one-stop-shop scan protocol combining brain computed tomography perfusion and head-and-neck computed tomography angiography using a 512-slice detector computed tomography scanner

AIM

To assess the efficiency and diagnostic value of the "real" one-stop-shop protocol integrating the computed tomography angiography (CTA) sequence of the head and neck into the computed tomography perfusion (CTP) acquisition using a 512-slice detector CT scanner in patients who suffered from acute ischemic stroke.

MATERIALS AND METHODS

This prospective study included 100 patients suspected of acute ischemic stroke. The patients were randomly divided into two groups: the control group (n=50) who underwent the traditional protocol (brain CTP and head-and-neck CTA examination separately) and the experimental group (n=50) who underwent a one-stop-shop protocol (combined brain CT perfusion and head-and-neck CTA, the CTA triggering time determined by a low-dose test bolus injection). The examination time, contrast-agent dosage, radiation dose, postprocessing time, and image quality were compared between the two groups.

RESULTS

Compared to the control group, the experimental group had a significantly lower total iodine contrast-agent dosage (80 vs. 100 ml, P<0.001) and shorter scan time (3.23 [3.13, 3.35] vs. 2.32 [2.17, 2.45] min, P<0.001). Additionally, the radiation dose exposure was lower in the experimental group than in the control group (5129.00 [5173, 5232] vs. 4681.35 [4555.12, 4822.95] mGy-cm, P<0.001). No statistically significant differences were observed between the two groups in terms of postprocessing time, head-and-neck CTA, and CTP imaging quality.

CONCLUSION

The one-stop-shop protocol enables effective detection of lesions, providing clear visualization of the location and degree of stenosis in the head-and-neck vessels. It achieves this with lower costs in scan time, contrast-agent dosage, and radiation dose compared to the traditional protocol and is thus worth considering as the first examination for patients who suffer from acute ischemic stroke.

A multicentre, randomized, double-blind, placebo-controlled trial of topical oestradiol gel for endometrial regeneration after induced abortion

STUDY QUESTION

Is topical oestradiol gel effective in promoting endometrial regeneration after a surgical abortion?

SUMMARY ANSWER

Topical oestradiol gel is effective in promoting endometrial regeneration after a surgical abortion with few side-effects.

WHAT IS KNOWN ALREADY

Oestrogen is effective in promoting endometrial regeneration. Transdermal oestrogen has been widely used in clinical practice for endometrial regeneration after induced abortion, but high-level evidence is limited.

STUDY DESIGN, SIZE, DURATION

We conducted a multicentre, superiority, randomized, double-blind, placebo-controlled trial. Between 9 March 2022 and 21 February 2023, 200 women were assigned in a 1:1 ratio to receive either oestradiol gel (treatment) and or oestradiol gel simulant (control) for 28 days. The participants were scheduled to have their endometrial thickness (mm) measured by ultrasonographic scan at 21-23 days post-abortion. The trial was blinded for participants, investigators, medical staff, and statistical analysts until final unblinding.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Participants were women undergoing induced abortion within 10 weeks of gestation. A total of 200 participants were enrolled, with 100 in each group. Eighty-eight (88%) in the treatment group and 82 (82%) in the control group completed the study as per the protocol and were included in the per-protocol set (PPS). The intent-to-treat (ITT) analysis included all participants randomized to the study groups and used inverse probability weighting to account for loss to follow-up.

MAIN RESULTS AND THE ROLE OF CHANCE

The ITT analysis showed revealed significantly greater endometrial thickness in the treatment group (mean 8.1 ± 2.5 mm) compared to the control group (mean 6.9 ± 2.1 mm) 21-23 days postabortion (mean difference 1.2 mm, 95% CI 0.7 to 1.9; P < 0.001). The median time to menstrual return was shorter in the treatment group (34 days, inter-quartile range [IQR] 30-38) than in the control group (35 days, IQR 32-42), with a difference of -1 day (95% CI -2.3 to -0.9; P = 0.036). No differences were observed in the timing or volume of bleeding in the first post-abortion cycle. The PPS analysis mirrored the ITT findings. Adverse events were minimal (6% versus 8%), and the blood profile, liver, kidney and coagulation test results were comparable between groups (all P > 0.05).

LIMITATIONS, REASONS FOR CAUTION

Loss to follow-up was 11% in the treatment group and 15% of controls, with no significant difference (P > 0.05). Inconsistencies in the timing of the ultrasonographic scans may have affected the accuracy of endometrial thickness measurements.

WIDER IMPLICATIONS OF THE FINDINGS

Our findings suggest that topical oestrogen supplementation immediately after abortion within the first 10 weeks of gestation improves endometrial regeneration and growth, thereby potentially increasing the chances of a successful subsequent pregnancy. Clinical application of these findings may improve endometrial health management practices and provide a perspective on fertility treatment and women's reproductive health.

STUDY FUNDING/COMPETING INTEREST(S)

This study was supported by a grant (FW-HKKT2021111501900) from Jianmin Pharmaceutical Group Co., Ltd (JMPG), Wuhan, Hubei, China. Both the oestradiol gel and the simulant were provided by JMPG. The funding source had no role in the study. X.Y.L. reports JMPG grant funding paid to their institutions. All other authors declare no competing interests.

TRIAL REGISTRATION NUMBER

CHiCTR2100053565.

TRIAL REGISTRATION DATE

24 November 2021.

DATE OF FIRST PATIENT’S ENROLMENT

9 March 2022.

[A lung sound classification model with a spatial and channel reconstruction convolutional module]

OBJECTIVE

To construct a model with a spatial and channel reconstruction convolutional module for accurate identification and classification of lung sound data.

METHODS

We propose a convolutional network architecture combining the spatial-channel reconstruction convolution (SCConv) module. A lung sound feature extraction method combining the dual tunable Q-factor wavelet transform (DTQWT) with the triple Wigner-Ville transform (WVT) was used to improve the model's ability to capture the key features of the lung sounds by adaptively focusing on the important channel and spatial features. The performance of the model for classification of normal, crackles, wheezes, and crackles with wheezes was tested using the ICBHI2017 dataset.

RESULTS AND CONCLUSION

The accuracy, sensitivity, specificity and F1 score of the proposed method reached 85.68%, 93.55%, 86.79% and 90.51%, respectively, demonstrating its good performance in classification tasks in the ICBHI2017 lung sound database, especially for distinguishing normal from abnormal lung sounds.

Hypothalamic vasopressin neural densities are higher in male Mongolian gerbils after separation from a pair bond partner and may facilitate behavior to form a new bond

Although pair bonding has been studied for several decades, only somewhat recently have researchers began studying the neural consequences of separation from a pair bond partner. Here we examined the impact of partner separation on the socially monogamous Mongolian gerbil. Using a within-subjects design, we assessed nonsocial, nonreproductive, and reproductive behavior in male gerbils pre- and post- either 4 weeks of cohabitation with or separation from a pair bond partner. We then conducted an immediate early gene study to examine the influence of partner separation on hypothalamic oxytocin and vasopressin neural responses to interactions with a novel, opposite-sex conspecific.

[Progress in cohort study of children and adolescents health]

Cohort study of children and adolescents health is an ideal method to explore health-related problems from childhood to adulthood, to which more attention has been paid. This paper summarizes the progress in cohort study of children and adolescents health conducted both at home and abroad by introducing the study design, main contents. Emphasizing the international exchange and cohort integration, continuously expanding cohort research field, and using multi-source data for high-quality follow-up have become the trend of cohort study of children and adolescents health.

Assessing morinidazole for surgical site infection in class III wounds prevention: a multi-centre, randomized, single-blind, parallel-controlled study

INTRODUCTION

Surgical site infections (SSIs) are significant postoperative risks; antibiotic prophylaxis is crucial due to the presence of anaerobic bacteria. This study investigated the efficacy and safety of a novel nitroimidazole, morinidazole, in SSI reduction in class III wounds, as there is currently a lack of evidence in the existing literature.

METHODS

A multi-centre randomized clinical trial was conducted from December 2020 to October 2022 in the general surgery departments of 12 tertiary hospitals in China, including 459 patients in two treatment groups using morinidazole plus ceftriaxone or ceftriaxone alone. Efficacy and safety were evaluated including SSI incidence, adverse events, and compliance. Statistical analysis employed SAS 9.4 software. Data analysis was performed from February to May 2023.

RESULTS

A total of 440 participants (median (interquartile range, IQR) age, 63.0 (54.0, 70.0) years; 282 males (64.09%); 437 patients were of Han race (99.32%) and were randomized. The experimental group exhibited a significantly lower SSI rate compared with the control group (31 (14.49%) vs 52 (23.01%); risk difference, 1.76%, 95% confidence interval (CI) 1.08-2.88%; P=0.0224). The superficial incisional site infections revealed a marked reduction in the experimental group (12 (5.61%) vs 31 (13.37%); risk difference, 2.68%; 95% CI 1.34-5.36%; P=0.0042). Non-surgical site infections, severe postoperative complications, and total adverse events showed no statistically significant differences between the groups (P>0.05).

CONCLUSION

The significant decrease in SSI rates and superficial incisional infections demonstrates morinidazole to be a valuable prophylactic antibiotic. Our findings provide valuable insights for clinical practice, where this new-generation nitroimidazole can play a crucial role in SSI prevention.

New application of saline contrast-enhanced electrical impedance tomography method for right ventriculography besides lung perfusion: detection of right-to-left intracardiac shunt

AIM

Saline contrast-enhanced electrical impedance tomography (EIT) has been used to identify the respiratory failure etiologies through assessment of regional lung perfusion at the bedside. In this study, we introduce a novel approach to detect right-to-left intracardiac shunt based on the center of heart (CoH) parameter determined from the early phase of impedance-time curve after saline bolus injection.

METHODS AND RESULT

The timepoints when the saline bolus enter the heart (T0) and the lung regions (T1) are identified at first. A moving time window from T0 to T1 is then generated with steps of 0.5 s and the slope of the impedance-time curve in each pixel within the window calculated. CoH is calculated as the geometric center of pixel slope values in the right-to-left image direction. To illustrate how this method works in practice, we calculated the CoH values at T0 to T1 in 10 control hypoxic patients with no right-to-left shunt. In addition, we examined two critically ill patients with right-to-left intracardiac shunt. One was postcardiac surgery patient who had a residual atrial septal defect by color doppler of transesophageal echocardiograph. The other patient had a congenital heart disease of ventricular septal defect by color doppler of trans-thoracic echocardiography. A large difference in CoH between T0 to T1 was observed in the two patients with intracardiac shunt than in the control patients (11.06 ± 3.17% vs. 1.99 ± 1.43%, P = 0.030).

CONCLUSION

Saline bolus EIT for lung perfusion might be used as ventriculography to identify the right-to-left intracardiac shunt at the bedside.

[Establishment and preliminary application of neutralizing antibody detection method for human respiratory syncytial virus]

Objective: To establish a Plaque-reduction Neutralization Test (PRNT) for the detection of neutralizing antibody titers of Human Respiratory Syncytial Virus (HRSV) and optimize the conditions for preliminary application. Methods: The CHO expression system was used to produce palivizumab monoclonal antibody (palivizumab) and the influencing factors such as cell type, cell culture duration, fixation and permeabilization protocols, and blocking agents. The reproducibility of the method was verified and its correlation was verified with conventional PRNT. Finally, the optimized PRNT assay was further used to determine neutralizing antibody titers against HRSV subtypes A and B in BALB/c mouse serum (immunized by intramuscular injection of HRSV fusion proteins). Results: Palivizumab was expressed at approximately 50 mg/L. The optimal working conditions for PRNT were as follows: culturing HEp-2 cells for 2 days, fixing with 4% (V/V) paraformaldehyde at room temperature for 15 min followed by 0.2% (V/V) Triton X-100 permeabilization for 15 minutes as the optimal fixation-permeabilization and removing the blocking step. The overall coefficient of variation (CV) for the reproducibility validation of this method was <15%, showing a good linear relationship with the conventional PRNT. The Spearman correlation coefficient rs was 0.983. This method was used to detect neutralizing antibody titers in mouse sera against HRSV subtype A strain long and subtype B strain 9320, and the fusion proteins combined with AlOH and CpG adjuvant induced the highest neutralizing antibody titers in mice. Conclusion: The HRSV neutralizing antibody assay established in this study is rapid, reproducible, high-throughput, and can be used to detect neutralizing antibodies to HRSV subtypes A and B.

Search for Periodic Time Variations of the Solar ^{8}B Neutrino Flux between 1996 and 2018 in Super-Kamiokande

We report a search for time variations of the solar ^{8}B neutrino flux using 5804 live days of Super-Kamiokande data collected between May 31, 1996, and May 30, 2018. Super-Kamiokande measured the precise time of each solar neutrino interaction over 22 calendar years to search for solar neutrino flux modulations with unprecedented precision. Periodic modulations are searched for in a dataset comprising five-day interval solar neutrino flux measurements with a maximum likelihood method. We also applied the Lomb-Scargle method to this dataset to compare it with previous reports. The only significant modulation found is due to the elliptic orbit of the Earth around the Sun. The observed modulation is consistent with astronomical data: we measured an eccentricity of (1.53±0.35)%, and a perihelion shift of (-1.5±13.5) days.

T staging esophageal tumors with x rays

With histopathology results typically taking several days, the ability to stage tumors during interventions could provide a step change in various cancer interventions. X-ray technology has advanced significantly in recent years with the introduction of phase-based imaging methods. These have been adapted for use in standard labs rather than specialized facilities such as synchrotrons, and approaches that enable fast 3D scans with conventional x-ray sources have been developed. This opens the possibility to produce 3D images with enhanced soft tissue contrast at a level of detail comparable to histopathology, in times sufficiently short to be compatible with use during surgical interventions. In this paper we discuss the application of one such approach to human esophagi obtained from esophagectomy interventions. We demonstrate that the image quality is sufficiently high to enable tumor T staging based on the x-ray datasets alone. Alongside detection of involved margins with potentially life-saving implications, staging tumors intra-operatively has the potential to change patient pathways, facilitating optimization of therapeutic interventions during the procedure itself. Besides a prospective intra-operative use, the availability of high-quality 3D images of entire esophageal tumors can support histopathological characterization, from enabling "right slice first time" approaches to understanding the histopathology in the full 3D context of the surrounding tumor environment.

Personalised follow-up and management schema for patients with screen-detected pulmonary nodules: A dynamic modelling study

BACKGROUND

Selecting the time target for follow-up testing in lung cancer screening is challenging. We aim to devise dynamic, personalized lung cancer screening schema for patients with pulmonary nodules detected through low-dose computed tomography.

METHODS

We developed and validated dynamic models using data of pulmonary nodule patients (aged 55-74 years) from the National Lung Screening Trial. We predicted patient-specific risk profiles at baseline (R0) and updated the risk evaluation results in repeated screening rounds (R1 and R2). We used risk cutoffs to optimize time-dependent sensitivity at an early decision point (3 months) and time-dependent specificity at a late decision point (1 year).

RESULTS

In validation, area under receiver operating characteristic curve for predicting 12-month lung cancer onset was 0.867 (95 % confidence interval: 0.827-0.894) and 0.807 (0.765-0.948) at R0 and R1-R2, respectively. The personalized schema, compared with National Comprehensive Cancer Network (NCCN) guideline and Lung-RADS, yielded lower rates of delayed diagnosis (1.7% vs. 1.7% vs. 6.9 %) and over-testing (4.9% vs. 5.6% vs. 5.6 %) at R0, and lower rates of delayed diagnosis (0.0% vs. 18.2% vs. 18.2 %) and over-testing (2.6% vs. 8.3% vs. 7.3 %) at R2. Earlier test recommendation among cancer patients was more frequent using the personalized schema (vs. NCCN: 29.8% vs. 20.9 %, p = 0.0065; vs. Lung-RADS: 33.2% vs. 22.8 %, p = 0.0025), especially for women, patients aged ≥65 years, and part-solid or non-solid nodules.

CONCLUSIONS

The personalized schema is easy-to-implement and more accurate compared with rule-based protocols. The results highlight value of personalized approaches in realizing efficient nodule management.

Structural performance of detachable precast concrete column-column joint

A novel type of detachable precast concrete column-column joint (DPC) is proposed in this study to solve the problems in current column-column dry connections including complex load path, uncertainty of structural stiffness of beam-column joints and inconvenience for disassembly. The dry connection technology is applied by composing of steel plate and concrete. Finite element models of DPC were created to study its structural performance including hysteresis curve, skeleton curve, ductility, and energy dissipation capacity. The benchmark models are firstly established and validated against the test data and after that a small-scale parametric study is prepared. The effect of axial pressure ratio and eccentricity distance size on the seismic performance of DPC was studied. Results indict that the optimal value of axial pressure ratio ranges from 0.5 to 0.7. With increase of the axial pressure ratio, the ductility coefficient shows a decreasing trend in general. The eccentricity has little effect on the energy dissipation capacity of the joint.

Computational Screening of a Single-Atom Catalyst Supported by Monolayer Nb2S2C for Oxygen Reduction Reaction

The search for high-performance catalysts to improve the catalytic activity for an oxygen reduction reaction (ORR) is crucial for developing a proton exchange membrane fuel cell. Using the first-principles method, we have performed computational screening on a series of transition metal (TM) atoms embedded in monolayer Nb2S2C to enhance the ORR activity. Through the scaling relationship and volcano plot, our results reveal that the introduction of a single Ni or Rh atom through substitutional doping into monolayer Nb2S2C yields promising ORR catalysts with low overpotentials of 0.52 and 0.42 V, respectively. These doped atoms remain intact on the monolayer Nb2S2C even at elevated temperatures. Importantly, the catalytic activity of the Nb2S2C doped with a TM atom can be effectively correlated with an intrinsic descriptor, which can be computed based on the number of d orbital electrons and the electronegativity of TM and O atoms.

Toripalimab plus axitinib versus sunitinib as first-line treatment for advanced renal cell carcinoma: RENOTORCH, a randomized, open-label, phase III study

BACKGROUND

Immune checkpoint inhibitors in combination with tyrosine kinase inhibitors are standard treatments for advanced clear cell renal cell carcinoma (RCC). This phase III RENOTORCH study compared the efficacy and safety of toripalimab plus axitinib versus sunitinib for the first-line treatment of patients with intermediate-/poor-risk advanced RCC.

PATIENTS AND METHODS

Patients with intermediate-/poor-risk unresectable or metastatic RCC were randomized in a ratio of 1 : 1 to receive toripalimab (240 mg intravenously once every 3 weeks) plus axitinib (5 mg orally twice daily) or sunitinib [50 mg orally once daily for 4 weeks (6-week cycle) or 2 weeks (3-week cycle)]. The primary endpoint was progression-free survival (PFS) assessed by an independent review committee (IRC). The secondary endpoints were investigator-assessed PFS, overall response rate (ORR), overall survival (OS), and safety.

RESULTS

A total of 421 patients were randomized to receive toripalimab plus axitinib (n = 210) or sunitinib (n = 211). With a median follow-up of 14.6 months, toripalimab plus axitinib significantly reduced the risk of disease progression or death by 35% compared with sunitinib as assessed by an IRC [hazard ratio (HR) 0.65, 95% confidence interval (CI) 0.49-0.86; P = 0.0028]. The median PFS was 18.0 months in the toripalimab-axitinib group, whereas it was 9.8 months in the sunitinib group. The IRC-assessed ORR was significantly higher in the toripalimab-axitinib group compared with the sunitinib group (56.7% versus 30.8%; P < 0.0001). An OS trend favoring toripalimab plus axitinib was also observed (HR 0.61, 95% CI 0.40-0.92). Treatment-related grade ≥3 adverse events occurred in 61.5% of patients in the toripalimab-axitinib group and 58.6% of patients in the sunitinib group.

CONCLUSION

In patients with previously untreated intermediate-/poor-risk advanced RCC, toripalimab plus axitinib provided significantly longer PFS and higher ORR than sunitinib and had a manageable safety profile TRIAL REGISTRATION: ClinicalTrials.gov NCT04394975.

Factors associated with nocturnal and diurnal glycemic variability in patients with type 2 diabetes: a cross-sectional study

PURPOSE

There is little information on factors that influence the glycemic variability (GV) during the nocturnal and diurnal periods. We aimed to examine the relationship between clinical factors and GV during these two periods.

METHODS

This cross-sectional study included 134 patients with type 2 diabetes. 24-h changes in blood glucose were recorded by a continuous glucose monitoring system. Nocturnal and diurnal GV were assessed by standard deviation of blood glucose (SDBG), coefficient of variation (CV), and mean amplitude of glycemic excursions (MAGE), respectively. Robust regression analyses were performed to identify the factors associated with GV. Restricted cubic splines were used to determine dose-response relationship.

RESULTS

During the nocturnal period, age and glycemic level at 12:00 A.M. were positively associated with GV, whereas alanine aminotransferase was negatively associated with GV. During the diurnal period, homeostatic model assessment 2-insulin sensitivity (HOMA2-S) was positively associated with GV, whereas insulin secretion-sensitivity index-2 (ISSI2) was negatively associated with GV. Additionally, we found a J-shape association between the glycemic level at 12:00 A.M. and MAGE, with 9.0 mmol/L blood glucose level as a cutoff point. Similar nonlinear associations were found between ISSI2 and SDBG, and between ISSI2 and MAGE, with ISSI2 value of 175 as a cutoff point.

CONCLUSION

Factors associated with GV were different between nocturnal and diurnal periods. The cutoff points we found in this study may provide the therapeutic targets for beta-cell function and pre-sleep glycemic level in clinical practice.

Personalized Computational Causal Modeling of the Alzheimer Disease Biomarker Cascade

BACKGROUND

Mathematical models of complex diseases, such as Alzheimer's disease, have the potential to play a significant role in personalized medicine. Specifically, models can be personalized by fitting parameters with individual data for the purpose of discovering primary underlying disease drivers, predicting natural history, and assessing the effects of theoretical interventions. Previous work in causal/mechanistic modeling of Alzheimer's Disease progression has modeled the disease at the cellular level and on a short time scale, such as minutes to hours. No previous studies have addressed mechanistic modeling on a personalized level using clinically validated biomarkers in individual subjects.

OBJECTIVES

This study aimed to investigate the feasibility of personalizing a causal model of Alzheimer's Disease progression using longitudinal biomarker data.

DESIGN/SETTING/PARTICIPANTS/MEASUREMENTS

We chose the Alzheimer Disease Biomarker Cascade model, a widely-referenced hypothetical model of Alzheimer's Disease based on the amyloid cascade hypothesis, which we had previously implemented mathematically as a mechanistic model. We used available longitudinal demographic and serial biomarker data in over 800 subjects across the cognitive spectrum from the Alzheimer's Disease Neuroimaging Initiative. The data included participants that were cognitively normal, had mild cognitive impairment, or were diagnosed with dementia (probable Alzheimer's Disease). The model consisted of a sparse system of differential equations involving four measurable biomarkers based on cerebrospinal fluid proteins, imaging, and cognitive testing data.

RESULTS

Personalization of the Alzheimer Disease Biomarker Cascade model with individual serial biomarker data yielded fourteen personalized parameters in each subject reflecting physiologically meaningful characteristics. These included growth rates, latency values, and carrying capacities of the various biomarkers, most of which demonstrated significant differences across clinical diagnostic groups. The model fits to training data across the entire cohort had a root mean squared error (RMSE) of 0.09 (SD 0.081) on a variable scale between zero and one, and were robust, with over 90% of subjects showing an RMSE of < 0.2. Similarly, in a subset of subjects with data on all four biomarkers in at least one test set, performance was high on the test sets, with a mean RMSE of 0.15 (SD 0.117), with 80% of subjects demonstrating an RMSE < 0.2 in the estimation of future biomarker points. Cluster analysis of parameters revealed two distinct endophenotypic groups, with distinct biomarker profiles and disease trajectories.

CONCLUSION

Results support the feasibility of personalizing mechanistic models based on individual biomarker trajectories and suggest that this approach may be useful for reclassifying subjects on the Alzheimer's clinical spectrum. This computational modeling approach is not limited to the Alzheimer Disease Biomarker Cascade hypothesis, and can be applied to any mechanistic hypothesis of disease progression in the Alzheimer's field that can be monitored with biomarkers. Thus, it offers a computational platform to compare and validate various disease hypotheses, personalize individual biomarker trajectories and predict individual response to theoretical prevention and therapeutic intervention strategies.

Assessing Near-Infrared Optical Tomography's Depth Capability in Imaging Brain Vessels: An Experimental Study

Advanced brain vessel imaging is crucial for diagnosing and treating brain-related conditions such as lesions and strokes, ultimately enhancing brain health. Among the range of cerebrovascular imaging modalities, near-infrared optical tomography (NIROT) stands out for its cost-effectiveness and brain oxygenation quantification. The objective of this project, as a continuation of our prior simulation study, is to evaluate in vitro the Pioneer system for imaging blood vessels. An experimental study was performed on a silicon phantom with a tube inclusion mimicking the superficial blood vessels at a depth of 5 mm. The experiment employed a time domain (TD) NIROT called Pioneer system. Image reconstruction was performed using the obtained TD data. We used root mean square error (RMSE) to evaluate the accuracy of the reconstructed images. We were able to detect the location and structure of the tube with a RMSE of 0.0285. This experimental study showed that the TD NIROT Pioneer system can detect vessel-like inclusion at the depth of 5 mm.

Clinical service evaluation of the feasibility and reproducibility of novel artificial intelligence based-echocardiographic quantification of global longitudinal strain and left ventricular ejection fraction in trastuzumab-treated patients

Introduction

Cardiotoxicity is a potential prognostically important complication of certain chemotherapeutic agents that may result in preclinical or overt clinical heart failure. In some cases, chemotherapy must be withheld when left ventricular (LV) systolic function becomes significantly impaired, to protect cardiac function at the expense of a change in the oncological treatment plan, leading to associated changes in oncological prognosis. Accordingly, patients receiving potentially cardiotoxic chemotherapy undergo routine surveillance before, during and following completion of therapy, usually with transthoracic echocardiography (TTE). Recent advancements in AI-based cardiac imaging reveal areas of promise but key challenges remain. There are ongoing questions as to whether the ability of AI to detect subtle changes in individual patients is at a level equivalent to manual analysis. This raises the question as to whether AI-based left ventricular strain analysis could provide a potential solution to left ventricular systolic function analysis in a manner equivocal to or superior to conventional assessment, in a real-world clinical service. AI based automated analyses may represent a potential solution for addressing the pressure of increasing echocardiographic demands within limited service-capacity healthcare systems, in addition to facilitating more accurate diagnoses.

Methods

This clinical service evaluation aims to establish whether AI-automated analysis compared to conventional methods (1) is a feasible method for assessing LV-GLS and LVEF, (2) yields moderate to good correlation between the two approaches, and (3) would lead to different clinical recommendations with serial surveillance in a real-world clinical population.

Results and Discussion

We observed a moderate correlation (r = 0.541) in GLS between AI automated assessment compared to conventional methods. The LVEF quantification between methods demonstrated a strong correlation (r = 0.895). AI-generated GLS and LVEF values compared reasonably well with conventional methods, demonstrating a similar temporal pattern throughout echocardiographic surveillance. The apical-three chamber view demonstrated the lowest correlation (r = 0.423) and revealed to be least successful for acquisition of GLS and LVEF. Compared to conventional methodology, AI-automated analysis has a significantly lower feasibility rate, demonstrating a success rate of 14% (GLS) and 51% (LVEF).

Erratum: Search for Cosmic-Ray Boosted Sub-GeV Dark Matter Using Recoil Protons at Super-Kamiokande [Phys. Rev. Lett. 130, 031802 (2023)]

This corrects the article DOI: 10.1103/PhysRevLett.130.031802.

Determining the Dosimetric Accuracy of Deep Learning-Based Fully Automated Registration-Segmentation Approach for Thoracic Cancer Organs-at-Risk Contouring

PURPOSE/OBJECTIVE(S)

For adaptive radiation therapy (ART), the contours on the planning CT (pCT) are frequently propagated to cone-beam CT (CBCT) via deformable image registration and manually edited, which is observer-dependent and time-consuming. To automate this process, we created a fully automated workflow by combining a deep learning (DL)-based pCT segmentation model with a CT-to-CBCT registration-segmentation DL model. The purpose of our research is to determine how using the proposed workflow's automatically generated contours affects thoracic organs-at-risk sparing (OAR).

MATERIALS/METHODS

Seven patients with locally advanced non-small cell lung cancer who underwent treatment with intensity modulated radiation therapy were included in this study. Each patient's pCT was segmented using a published DL model that has been used for generating thoracic OAR segmentation and radiotherapy planning in the clinic since July of 2020. Next, pCT was deformably registered using a published recurrent deep registration-segmentation method. Whereas the original method's segmentation sub-network was only trained to segment esophagus, the registration sub-network was used to propagate contours for heart, esophagus, and the proximal bronchial tree (PBT). Geometric segmentation accuracy using the Dice Similarity Coefficient (DSC) and the 95th percentile Hausdorff Distance (HD) and dose metrics including the mean esophageal dose (MED) and D90% of the heart (D90) were computed from the total accumulated dose for the first two weeks of treatment.

RESULTS

The esophagus had a high DSC and a low HD (0.93 and 2.85mm) and conversely, the heart had lower accuracy (DSC = 0.85, HD = 22.06mm). PBT showed relatively high performance as well, with DSC of 0.91 and HD of 2.28mm, owing to its proximity to the esophagus. The accumulated MED for manual contour was slightly lower than AI-contours (11.34 vs 11.83 Gy), suggesting reliability of the proposed workflow. The reverse is seen for the D90 of the heart (manual = 1.74 and AI-contour = 1.56 Gy), likely due to the heart not being included in the original DL framework.

CONCLUSION

This study reported preliminary results on the feasibility of using a fully automated and patient-specific workflow for CBCT auto-segmentation in ART, confirming its role as a geometrically and dosimetrically accurate solution for thoracic OARs. However, because it is currently limited to the esophagus, we believe that re-training the algorithm will increase confidence in other OARs such as the heart and lungs.

Clinical Feasibility of Deep Learning-Based CT during Treatment CBCT Tumor Registration-Segmentation in Thoracic Radiotherapy (RT)

PURPOSE/OBJECTIVE(S)

Accurate tumor segmentation on weekly cone-beam computed tomography (CBCT) images is critical for image-guided and adaptive radiation therapy (ART). In thoracic RT, low image contrast, imaging artifact, and geometry and image modality differences from the planning CT (pCT) typically limits accurate tumor segmentation and registration. Here, we explored the clinical feasibility of using 3D recurrent registration-segmentation deep learning (DL) that combines patient-specific anatomic and shape context from higher contrast pCT and planning contours (PACs) for tumor segmentation on during treatment CBCTs.

MATERIALS/METHODS

We included the pCT and CBCTs from six patients with locally advanced non-small cell lung cancer (LA-NSCLC) who had underwent RT. Cases were selected with a primary GTV contoured and labeled separately from the nodal GTV. Using rigidly aligned pCT and CBCT as inputs, DL auto-segmented the GTV on week 1 and 6 CBCTs, and these auto-segmented contours were manually inspected by a radiation oncologist that edited the GTV according to clinical standard quality. The Dice similarity coefficient (DSC), Hausdorff distance (HD95), mean surface distance (MSD), surface DSC (sDSC) and added path length (APL) were used to quantitively compare the DL and the edited GTV.

RESULTS

The primary GTV was in the right lung in five cases, and left lung in one case. Manual adjustments were typically made at the interface of GTV and lung parenchyma with partial inclusion of adjacent vessels. Hypodensities within the GTV were sometimes not segmented in all axial slices resulting in discontinuous components. The quantitative comparison between the edited and DL-generated GTV is shown in Table 1. For week 1, the average DSC and HD95 were 0.87 and 6.94 mm, respectively. The performance for week 6 was slightly lower than week 1, with a DSC of 0.85 and HD95 of 7.22 mm.

CONCLUSION

The agreement with the generated DL GTV and the edited GTV was high in week 1 and decreased somewhat later during the treatment course possibly due to a higher impact of geometric changes in tumor and adjacent structures. The proposed DL algorithm showed reasonable performance throughout the treatment, supporting its potential for use into clinical routine for LA-NSCLC.

Augmenting Prediction of Intracranial Aneurysms' Risk Status Using Velocity-Informatics: Initial Experience

Our primary goal here is to demonstrate that innovative analytics of aneurismal velocities, named velocity-informatics, enhances intracranial aneurysm (IA) rupture status prediction. 3D computer models were generated using imaging data from 112 subjects harboring anterior IAs (4-25 mm; 44 ruptured and 68 unruptured). Computational fluid dynamics simulations and geometrical analyses were performed. Then, computed 3D velocity vector fields within the IA dome were processed for velocity-informatics. Four machine learning methods (support vector machine, random forest, generalized linear model, and GLM with Lasso or elastic net regularization) were employed to assess the merits of the proposed velocity-informatics. All 4 ML methods consistently showed that, with velocity-informatics metrics, the area under the curve and prediction accuracy both improved by approximately 0.03. Overall, with velocity-informatics, the support vector machine's prediction was most promising: an AUC of 0.86 and total accuracy of 77%, with 60% and 88% of ruptured and unruptured IAs being correctly identified, respectively.

Correlation between nocturnal intermittent hypoxemia and mild cognitive impairment in the older adult and the role of BDNF Val66Met polymorphism: a hospital-based cross-sectional study

PURPOSE

To explore the prevalence of nocturnal intermittent hypoxemia (NIH) in a tertiary hospital geriatric department and the relationship between NIH and mild cognitive impairment (MCI) in older adults, and to examine the role of brain-derived neurotrophic factor (BDNF) Val66Met polymorphism.

METHODS

Older adults aged ≥ 60 were enrolled. NIH and cognitive assessments were conducted. BDNF concentrations and BDNF Val66Met polymorphism were detected for a preliminary exploration of the possible mechanism of the process.

RESULTS

Of 325 older adults enrolled, 157 (48%) had NIH and were further divided into mild, moderate, and severe NIH groups according to their oxygen desaturation of ≥ 4% per hour of sleep (ODI4). MCI detection rate in the four groups gradually increased, and the differences were statistically significant (chi-square = 4.457, P = 0.035). ODI4 was negatively correlated with MoCA score in all participants (r =  - 0.115, P = 0.039) and patients with NIH (r =  - 0.199, P = 0.012). After adjusting for sex, age, and cardiovascular risk factors, NIH and MCI remained independently associated (OR = 3.13, 95% CI 1.03-9.53, P = 0.045). BDNF levels were positively correlated with MoCA score (r = 0.169, P = 0.028) and negatively correlated with nocturnal average oxygen saturation in patients with NIH (r =  - 0.288, P = 0.008). Older adults with different BDNF Val66Met genotypes did not show significant differences in MCI rate and BDNF levels (P > 0.05).

CONCLUSION

The older adults with NIH have a higher MCI detection rate. BDNF levels may be a potential biomarker for cognitive dysfunction in patients with NIH.