First direct machine-specific parameters incorporated in Spot-scanning Proton Arc (SPArc) optimization algorithm.

BACKGROUND: Spot-scanning Proton Arc (SPArc) has been of significant interest in recent years because of its superior plan quality. Currently, the primary focus of research and development is on deliverability and treatment efficiency. PURPOSE: To address the challenges in generating a deliverable and efficient SPArc plan for a proton therapy system with a massive gantry, we developed a novel SPArc optimization algorithm (SPArcDMPO ) by directly incorporating the machine-specific parameters such as gantry mechanical constraints and proton delivery sequence. METHODS: SPArc delivery sequence model (DSMarc ) was built based on the machine-specific parameters of the prototype arc delivery system, IBA ProteusONE®, including mechanical constraint (maximum gantry speed, acceleration, and deceleration) and proton delivery sequence (energy and spot delivery sequence, and irradiation time). SPArcDMPO resamples and adjusts each control point's delivery speed based on the DSMarc calculation through the iterative approach. In SPArcDMPO, users could set a reasonable arc delivery time during the plan optimization, which aims to minimize the gantry momentum changes and improve the delivery efficiency. Ten cases were selected to test SPArcDMPO . Two kinds of SPArc plans were generated using the same planning objective functions: (1) original SPArc plan (SPArcoriginal ); (2) SPArcDMPO plan with a user-pre-defined delivery time. Additionally, arc delivery sequence was simulated based on the DSMarc and was compared. Treatment delivery time was compared between SPArcoriginal and SPArcDMPO . Dynamic arc delivery time, the static irradiation time, and its corresponding time differential (time differential = dynamic arc delivery time-static irradiation time) were analyzed, respectively. The total gantry velocity change was accumulated throughout the treatment delivery. RESULTS: With a similar plan quality, objective value, number of energy layers, and spots, both SPArcoriginal and SPArcDMPO plans could be delivered continuously within the ± 1 degree tolerance window. However, compared to the SPArcoriginal , the strategy of SPArcDMPO is able to reduce the time differential from 30.55 ± 11.42%(90 ± 32 s) to 14.67 ± 6.97%(42 ± 20 s), p < 0.01. Furthermore, the corresponding total variations of gantry velocity during dynamic arc delivery are mitigated (SPArcoriginal vs. SPArcDMPO ) from 14.73 ± 9.14 degree/s to 4.28 ± 2.42 degree/s, p < 0.01. Consequently, the SPArcDMPO plans could minimize the gantry momentum change based on the clinical user's input compared to the SPArcoriginal plans, which could help relieve the mechanical challenge of accelerating or decelerating the massive proton gantry. CONCLUSIONS: For the first time, clinical users not only could generate a SPArc plan meeting the mechanical constraint of their proton system but also directly control the arc treatment speed and momentum changes of the gantry during the plan optimization process. This work paved the way for the routine clinical implementation of proton arc therapy in the treatment planning system.

Optimizing linear energy transfer distribution in intensity-modulated proton therapy using the alternating direction method of multipliers.

Purpose: This study develop a novel linear energy transfer (LET) optimization method for intensity-modulated proton therapy (IMPT) with minimum monitor unit (MMU) constraint using the alternating direction method of multipliers (ADMM). Material and methods: The novel LET optimization method (ADMM-LET) was proposed with (1) the dose objective and the LET objective as the optimization objective and (2) the non-convex MMU threshold as a constraint condition. ADMM was used to solve the optimization problem. In the ADMM-LET framework, the optimization process entails iteratively solving the dose sub-problem and the LET sub-problem, simultaneously ensuring compliance with the MMU constraint. Three representative cases, including brain, liver, and prostate cancer, were utilized to evaluate the performance of the proposed method. The dose and LET distributions from ADMM-LET were compared to those obtained using the published iterative convex relaxation (ICR-LET) method. Results: The results demonstrate the superiority of ADMM-LET over ICR-LET in terms of LET distribution while achieving a comparable dose distribution. More specifically, for the brain case, the maximum LET (unit: keV/µm) at the optic nerve decreased from 5.45 (ICR-LET) to 1.97 (ADMM-LET). For the liver case, the mean LET (unit: keV/µm) at the clinical target volume increased from 4.98 (ICR-LET) to 5.50 (ADMM-LET). For the prostate case, the mean LET (unit: keV/µm) at the rectum decreased from 2.65 (ICR-LET) to 2.14 (ADMM-LET). Conclusion: This study establishes ADMM-LET as a new approach for LET optimization with the MMU constraint in IMPT, offering potential improvements in treatment outcomes and biological effects.

Carbohydrate antigen 125 in congestive heart failure: ready for clinical application?

Congestion is the permanent mechanism driving disease progression in patients with acute heart failure (AHF) and also is an important treatment target. However, distinguishing between the two different phenotypes (intravascular congestion and tissue congestion) for personalized treatment remains challenging. Historically, carbohydrate antigen 125 (CA125) has been a frequently used biomarker for the screening, diagnosis, and prognosis of ovarian cancer. Interestingly, CA125 is highly sensitive to tissue congestion and shows potential for clinical monitoring and optimal treatment of congestive heart failure (HF). Furthermore, in terms of right heart function parameters, CA125 levels are more advantageous than other biomarkers of HF. CA125 is expected to become a new biological alternative marker for congestive HF and thereby is expected be widely used in clinical practice.

Safety profile of intravenous digoxin in Chinese patients with acute heart failure with reduced ejection fraction: a small-scale prospective cohort study.

Background: Adverse effects of intravenous digoxin vary from patients and disease status, which should be closely monitored. Aims: To explore the safety profile of intravenous digoxin in acute heart failure with reduced ejection fraction (HFrEF) among Chinese patients. Methods: A clinical prospective, single-center, single-arm, open-label exploratory clinical trial was performed in patients with acute HFrEF at Wuhan Asia Heart Hospital. A fixed dose of 0.5 mg digoxin was used intravenously once per day for 3 days. The normalized dosage of digoxin (NDD), toxic serum digoxin concentration (SDC), and adverse reactions of intravenous digoxin were recorded. Results: A total of 40 patients were recruited in the study. The SDC increased from 1.03 ± 0.34 ng/mL to 1.95 ± 0.52 ng/mL during treatment. 50% (20/40) patients reached a toxic SDC of 2.0 ng/mL, and toxic effects were seen in 30% (12/40) patients. Estimated glomerular filtration rate (eGFR) < 60 mL/min [HR: 5.269; 95% CI: 1.905-14.575, p = 0.001], NDD ≥7 µg/kg [HR: 3.028; 95% CI: 1.119-8.194, p = 0.029], and ischemic cardiomyopathy [HR: 2.658; 95% CI: 1.025-6.894, p = 0.044] were independent risk factors for toxic SDC. Toxic SDC was effectively identified [area under the receiver operating characteristic (ROC) curve = 0.85, p < 0.001] using this model, and patients would have a higher risk of toxicity with more risk factors. Conclusion: Intravenous digoxin of 0.5 mg was safe and effective for initial dose but not suitable for maintenance treatment in Chinese patients with acute HFrEF. Patients who had lower eGFR, received higher NDD, and had ischemic cardiomyopathy should be closely monitored to avoid digoxin toxicity.

A novel planning framework for efficient spot-scanning proton arc therapy via particle swarm optimization (SPArc-particle swarm).

Objective.Delivery efficiency is the bottleneck of spot-scanning proton arc therapy (SPArc) because of the numerous energy layers (ELs) ascending switches. This study aims to develop a new algorithm to mitigate the need for EL ascending via water equivalent thickness (WET) sector selection followed by particle swarm optimization (SPArc-particle swarm).Approach.SPArc-particle swarmdivided the full arc trajectory into the optimal sectors based on K-means clustering analysis of the relative mean WET. Within the sector, particle swarm optimization was used to minimize the total energy switch time, optimizing the energy selection integrated with the EL delivery sequence and relationship. This novel planning framework was implemented on the open-source platform matRad (Department of Medical Physics in Radiation Oncology, German Cancer Research Center-DKFZ). Three representative cases (brain, liver, and prostate cancer) were selected for testing purposes. Two kinds of plans were generated: SPArc_seq and SPArc-particle swarm. The plan quality and delivery efficiency were evaluated.Main results. With a similar plan quality, the delivery efficiency was significantly improved using SPArc-particle swarmcompared to SPArc_seq. More specifically, it reduces the number of ELs ascending switching compared to the SPArc_seq (from 21 to 7 in the brain, from 21 to 5 in the prostate, from 21 to 6 in the liver), leading to a 16%-26% reduction of the beam delivery time (BDT) in the SPArc treatment.Significance. A novel planning framework, SPArc-particle swarm, could significantly improve the delivery efficiency, which paves the roadmap towards routine clinical implementation.

Evaluation of D-dimer in the diagnosis of suspected aortic dissection.

BACKGROUND: The goal of this study was to evaluate plasma D-dimer as a diagnostic marker for exclusion of suspected aortic dissection (AD). METHODS: Two-hundred and sixty suspected AD patients were enrolled, including acute AD, n=107; chronic AD, n=17; acute myocardial infarction (AMI), n=70; pulmonary embolism (PE), n=18; non-ST elevation myocardial infarction (NSTEMI), n=28; and unstable angina (UA), n=20. All patients had D-dimer testing performed (Roche Diagnostics GmbH) immediately following admission. RESULTS: The D-dimer concentrations in both the acute AD group [median: 3.47; 95% confidence interval (CI): 2.43-4.50 µg/mL] and chronic AD group (median: 1.09; 95% CI: 0.36-3.81 µg/mL) were significantly higher than those in patients in the AMI, NSTEMI and UA groups (p=0.000), but not when compared to the PE group. One (0.8%) patient was identified in the acute AD group who presented with a low D-dimer value (0.04 µg/mL), indicating the existence of intramural hematoma as demonstrated by CT. CONCLUSIONS: D-dimer may be used as a potential marker for suspected AD, with high sensitivity of up to 99.2% (1/124). Regardless of the cut-off threshold selected, the sensitivity of D-dimer was unable to reach 100%. Further examinations, including imaging technology, were necessary to diagnose the suspected AD patients who had negative D-dimer result.

D-dimer levels on admission to predict in-hospital mortality in patients with Covid-19.

BACKGROUND: The outbreak of the coronavirus disease 2019 (Covid-19) has shown a global spreading trend. Early and effective predictors of clinical outcomes are urgently needed to improve management of Covid-19 patients. OBJECTIVE: The aim of the present study was to evaluate whether elevated D-dimer levels could predict mortality in patients with Covid-19. METHODS: Patients with laboratory confirmed Covid-19 were retrospective enrolled in Wuhan Asia General Hospital from January 12, 2020, to March 15, 2020. D-dimer levels on admission and death events were collected to calculate the optimum cutoff using receiver operating characteristic curves. According to the cutoff, the subjects were divided into two groups. Then the in-hospital mortality between two groups were compared to assess the predictive value of D-dimer level. RESULTS: A total of 343 eligible patients were enrolled in the study. The optimum cutoff value of D-dimer to predict in-hospital mortality was 2.0 µg/mL with a sensitivity of 92.3% and a specificity of 83.3%. There were 67 patients with D-dimer ≥2.0 µg/mL, and 267 patients with D-dimer <2.0 µg/mL on admission. 13 deaths occurred during hospitalization. Patients with D-dimer levels ≥2.0 µg/mL had a higher incidence of mortality when comparing with those who with D-dimer levels <2.0 µg/mL (12/67 vs 1/267, P < .001; hazard ratio, 51.5; 95% confidence interval, 12.9-206.7). CONCLUSIONS: D-dimer on admission greater than 2.0 µg/mL (fourfold increase) could effectively predict in-hospital mortality in patients with Covid-19, which indicated D-dimer could be an early and helpful marker to improve management of Covid-19 patients. (Chinese Clinical Trial Registry: ChiCTR2000031428).