A Prospective Longitudinal Cohort Study of Serum Stanniocalcin-1 as a Potential Prognostic Biomarker of Severe Traumatic Brain Injury.

Background: Stanniocalcin-1 (STC1) may harbor anti-inflammatory and anti-oxidative properties, thereby exerting neuroprotective effects. This study was done with the intent to determine the role of serum STC1 in severity assessment and prognosis prediction of severe traumatic brain injury (sTBI). Methods: In this prospective longitudinal cohort study of 104 sTBI patients and 104 healthy individuals (controls), serum STC1 levels were quantified. Severity indicators were Glasgow Coma Scale (GCS) and Rotterdam computed tomography classification. Follow-up time was 180 days and extended Glasgow outcome scale (GOSE) score 1-4 was deemed as poor prognosis. Multivariate analyses were applied to assess severity correlations and prognosis associations. Discriminative efficiencies were estimated in terms of area under receiver operating characteristic curve (AUC). Results: Patients exhibited significantly higher serum STC1 levels than controls. Serum STC1 levels were substantially elevated in order of GCS scores from 8 to 3, Rotterdam scores from 3 to 6 and 180-day GOSE scores from 8 to 1. Also, serum STC1 levels were independently correlated with GCS scores, Rotterdam scores and 180-day GOSE scores. Serum STC1 levels were independently associated with 180-day death, overall survival and poor prognosis, as well as were efficiently predictive of death and poor prognosis. Prediction model containing GCS scores, Rotterdam scores and serum STC1 levels, as opposed to any of them, showed higher discriminative ability for the risks of death and poor prognosis. Alternatively, serum STC1 levels were linearly correlated with risk of death, overall survival and poor prognosis under restricted cubic spline. Subgroup analysis showed that serum STC1 levels non-statistically significantly interacted with age, gender, hypertension, diabetes mellitus, etc. Conclusion: A significant elevation of serum STC1 levels is highly related to severity and clinical outcome, suggesting that serum STC1 may be a potential prognostic biomarker of sTBI.

Dosimetric Features of Ultra-Hypofractionated Intensity Modulated Proton Therapy for Prostate Cancer.

Purpose: To report clinical and dosimetric characteristics of 5-fraction stereotactic ablative radiotherapy (SABR) using intensity modulated proton therapy (IMPT) for localized prostate cancer. Materials and Methods: All patients receiving IMPT SABR from 2017 to 2021 for localized prostate cancer at our institution were included. Five fractions were delivered every other day to the prostate +/- seminal vesicles [clinical target volume (CTV)] with 3 mm/3% robustness. A 4-field arrangement with 2 anterior oblique and 2 opposed lateral beams was used in most patients (97%), and most (99%) had a retroprostatic hydrogel spacer. Results: A total of 534 patients with low (14%), favorable intermediate (45%), unfavorable intermediate (36%), high (4.0%), or very high-risk (0.6%) disease are evaluated. Prescription dose was 36.25 Gy (31%), 38 Gy (38%), or 40 Gy (31%) was prescribed. Median volume percentage of CTV receiving at least 100% of prescription dose [V100% (%)] was 100% [interquartile range: 99.99-100]. Rectum V50% (%), V80% (%), and V90% (%) were significantly lower in patients who had spacer, with a mean difference of -9.70%, -6.59%, and -4.42%, respectively, compared to those who did not have spacer. Femoral head dose was lower with a 4-field arrangement. Mean differences in left and right femoral head V40% (%) were -6.99% and -10.74%, respectively. Conclusion: We provide a large, novel report of patients treated with IMPT SABR for localized prostate cancer. Four-field IMPT with hydrogel spacer provides significant sparing of rectum and femoral heads without compromising target coverage.

The effects of volatile anesthetics and propofol in patients undergoing off-pump coronary artery bypass grafting: a systematic review and meta-analysis.

Background: Studies investigating the cardioprotective effect of volatile anesthetics on cardiac troponins in off-pump coronary artery bypass grafting (OPCAB) surgery remain controversial. This current study was conducted to systematically evaluate the impact of volatile anesthetics and propofol on patients undergoing OPCAB surgery. Methods: A computerized search of electronic databases was conducted up to July 21, 2023, to identify relevant studies using appropriate search terms. The primary outcomes of interest were the levels of myocardial injury biomarkers (e.g., cTnI, cTnT), while secondary outcomes included extubation time, length of ICU stay, 30-day mortality, transfusion and thrombosis, and postoperative recovery, which were compared between two anesthesia techniques. Results: A search of databases produced 14 relevant studies with a combined total of 703 patients. Among them, 355 were allocated to the volatile anesthetics group and 348 to the propofol group. Our study reveals a statistically significant reduction in myocardial injury biomarkers among patients who received volatile anesthetics compared to those who received propofol (P < .001). Subgroup analysis showed that patients using sevoflurane had lower postoperative cardiac troponins levels compared to propofol (P = .01). However, desflurane and isoflurane currently have no significant advantage over propofol (all P > 0.05). There was no significant difference in postoperative mechanical ventilation time, length of ICU stay, and mortality between the two groups (all P > 0.05). Conclusions: This study suggested that volatile anesthetics, specifically sevoflurane, in adult OPCAB surgery provide a better cardioprotective effect than propofol. Systematic Review Registration: PROSPERO (CRD42023444277).

Serum concentrations of NLRP3 in relation to functional outcome and delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage.

BACKGROUND: Nucleotide-binding oligomerization domain-like receptor family pyrin domain-containing 3 (NLRP3) participates in neuroinflammation. We endeavored to determine the role of serum NLRP3 as a biomarker of neuroinflammation, severity, delayed cerebral ischemia (DCI) and functional outcome following aneurysmal subarachnoid hemorrhage (aSAH). METHODS: In this prospective and observational study, a total of 118 aSAH patients and 118 healthy volunteers were enrolled. Serum NLRP3 concentrations, blood glucose concentrations, serum C-reactive protein concentrations, and blood leucocyte counts were quantified. A poor outcome was defined as extended Glasgow outcome scale scores of 1-4 at post-injury 90 days. RESULTS: As compared to controls, significantly increased serum NLRP3 concentrations after aSAH were intimately correlated with the Glasgow coma scale scores, World Federation of Neurological Surgeons scale scores, Hunt-Hess scores, modified Fisher scores, extended Glasgow outcome scale scores, blood glucose concentrations, serum C-reactive protein concentrations and blood leucocyte counts. Serum NLRP3 emerged as an independent predictor for DCI and poor 90-day outcome. Using receiver operating characteristic curve, serum NLRP3 concentrations were significantly predictive of DCI and poor 90-day outcome. Its prognostic predictive ability was comparable to those of the Glasgow coma scale scores, World Federation of Neurological Surgeons scale scores, Hunt-Hess scores and modified Fisher scores. CONCLUSIONS: Serum NLRP3 may represent an inflammatory biomarker in relation to the severity, DCI and poor functional outcome after aSAH.

Nuclear Fragmentation Imaging for Carbon-Ion Radiation Therapy Monitoring: an In Silico Study.

Purpose: This article presents an in vivo imaging technique based on nuclear fragmentation of carbon ions in irradiated tissues for potential real-time monitoring of carbon-ion radiation therapy (CIRT) treatment delivery and quality assurance purposes in clinical settings. Materials and Methods: A proof-of-concept imaging and monitoring system (IMS) was devised to implement the technique. Monte Carlo simulations were performed for a prospective pencil-beam scanning CIRT nozzle. The development IMS benchmark considered a 5×5-cm2 pixelated charged-particle detector stack positioned downstream from a target phantom and list-mode data acquisition. The abundance and production origins, that is, vertices, of the detected fragments were studied. Fragment trajectories were approximated by straight lines and a beam back-projection algorithm was built to reconstruct the vertices. The spatial distribution of the vertices was then used to determine plan relevant markers. Results: The IMS technique was applied for a simulated CIRT case, a primary brain tumor. Four treatment plan monitoring markers were conclusively recovered: a depth dose distribution correlated profile, ion beam range, treatment target boundaries, and the beam spot position. Promising millimeter-scale (3-mm, ≤10% uncertainty) beam range and submillimeter (≤0.6-mm precision for shifts <3 cm) beam spot position verification accuracies were obtained for typical therapeutic energies between 150 and 290 MeV/u. Conclusions: This work demonstrated a viable online monitoring technique for CIRT treatment delivery. The method's strong advantage is that it requires few signal inputs (position and timing), which can be simultaneously acquired with readily available technology. Future investigations will probe the technique's applicability to motion-sensitive organ sites and patient tissue heterogeneities. In-beam measurements with candidate detector-acquisition systems are ultimately essential to validate the IMS benchmark performance and subsequent deployment in the clinic.

Intensity-Modulated Proton Therapy (IMPT) Treatment of Angiosarcoma of the Face and Scalp.

PURPOSE: To successfully plan and treat a patient with diffuse angiosarcoma involving the face and scalp with intensity-modulated proton therapy (IMPT) before surgical resection. MATERIALS AND METHODS: A patient presented to the radiation oncology department for preoperative treatment of an angiosarcoma diffusely involving the face and scalp. A 4-field IMPT technique was used to create a homogeneous dose distribution to the entire target volume while sparing underlying critical structures from toxicity and low-dose spread. A custom Monte Carlo optimizer was necessary to achieve treatment goals. Biological dose was evaluated with a linear energy transfer-based biological enhancement model. Robustness criteria were evaluated per department standard. The patient was successfully planned and treated according to clinical goals. RESULTS: The patient successfully completed the course of IMPT and was able to undergo surgical resection. Pathology indicated no presence of angiosarcoma. CONCLUSION: IMPT using a custom Monte Carlo optimizer is a suitable radiation therapy treatment option for patients with diffuse angiosarcoma of the scalp and face.

Robust radiobiological optimization of ion beam therapy utilizing Monte Carlo and microdosimetric kinetic model.

To develop a Monte Carlo (MC)-based and robust ion beam therapy optimization system that separates the optimization algorithm from the relative biological effectiveness (RBE) modeling. Robustly optimized dose distributions were calculated and compared across three ion therapy beams (proton, helium, carbon). The effect of different averaging techniques in calculating RBE in mixed beams was also investigated. Ion particles were transported in TOPAS MC. The microdosimetric-kinetic model (MKM) parameter, saturation corrected specific energy ([Formula: see text]), was calculated with a customized MKM implementation in TOPAS MC. Intensity modulated ion therapy robust optimization was performed by a quasi-Newton iterative method based on dose-volume objective function. The robust optimization took setup and range uncertainties into account. In the present work, the biological dose for each individual spot was calculated, and then summed together to calculate total biological dose. In other published works, radiosensitive parameters, such as [Formula: see text], were first averaged over all beam spots within a mixed-beam field, after which biological dose was calculated using the averaged radiosensitive parameters. The difference between the two mixed-beam biological dose calculations was quantified. Robust plans were achieved with the three particle types. The effect of averaging [Formula: see text] depended on particle type. The difference between biological doses calculated with individual [Formula: see text] and averaged [Formula: see text] may be greater than 3% for a carbon beam. MC based radiobiological and robust optimization was made flexible to incorporate dose-volume histogram constraints and to be independent of RBE models. Iterative optimization with RBE models was feasible. Evaluation of the RBE calculation for mixed beam could be necessary if better accuracy was demanded.

A robust intensity modulated proton therapy optimizer based on Monte Carlo dose calculation.

PURPOSE: Accuracy of dose calculation models and robustness under various uncertainties are key factors influencing the quality of intensity modulated proton therapy (IMPT) plans. To mitigate the effects of uncertainties and to improve the dose calculation accuracy, an all-scenario robust IMPT optimization based on accurate Monte Carlo (MC) dose calculation was developed. METHODS: In the all-scenario robust IMPT optimization, dose volume histograms (DVHs) were computed for the nominal case and for each uncertainty scenario. All scenarios were weighted by DVH values dynamically throughout optimization iterations. In contrast, probabilistic approach weighted scenarios with fixed scenario weights and worst case optimizations picked one single scenario - the worst scenario for each iteration. Uncertainties in patient setup and proton range were considered in all clinical cases studied. Graphics processing unit (GPU) computation was employed to reduce the computational time in both the MC dose calculation and optimization stages. A previously published adaptive quasi-Newton method for proton optimization was extended to include robustness. To validate the all-scenario algorithm extension, it was compared with the single scenario optimization target volume (OTV) based approach in clinical cases of three different disease sites. Additional comparisons with worst case optimization methods were conducted to evaluate the performance of the all-scenario robust optimization against other robust optimizations. RESULTS: The all-scenario robust IMPT optimization spared organs at risk (OARs) better than the OTV-based method while maintaining target coverage and improving the robustness of targets and OARs. Compared with composite and voxel-wise worst case optimization, the all-scenario robust optimization converged faster, and arrived at solutions of tighter DVH robustness spread, better target coverage and lower OAR dose. CONCLUSION: An all-scenario robust IMPT treatment planning system was developed using an adaptive quasi-Newton optimization method. The optimization system was GPU-accelerated and based on MC dose calculation. Improved performance was observed in clinical cases when compared with worst case optimization methods.

Clinically Applicable Monte Carlo-based Biological Dose Optimization for the Treatment of Head and Neck Cancers With Spot-Scanning Proton Therapy.

PURPOSE: Our aim is to demonstrate the feasibility of fast Monte Carlo (MC)-based inverse biological planning for the treatment of head and neck tumors in spot-scanning proton therapy. METHODS AND MATERIALS: Recently, a fast and accurate graphics processor unit (GPU)-based MC simulation of proton transport was developed and used as the dose-calculation engine in a GPU-accelerated intensity modulated proton therapy (IMPT) optimizer. Besides dose, the MC can simultaneously score the dose-averaged linear energy transfer (LETd), which makes biological dose (BD) optimization possible. To convert from LETd to BD, a simple linear relation was assumed. By use of this novel optimizer, inverse biological planning was applied to 4 patients, including 2 small and 1 large thyroid tumor targets, as well as 1 glioma case. To create these plans, constraints were placed to maintain the physical dose (PD) within 1.25 times the prescription while maximizing target BD. For comparison, conventional intensity modulated radiation therapy (IMRT) and IMPT plans were also created using Eclipse (Varian Medical Systems) in each case. The same critical-structure PD constraints were used for the IMRT, IMPT, and biologically optimized plans. The BD distributions for the IMPT plans were obtained through MC recalculations. RESULTS: Compared with standard IMPT, the biologically optimal plans for patients with small tumor targets displayed a BD escalation that was around twice the PD increase. Dose sparing to critical structures was improved compared with both IMRT and IMPT. No significant BD increase could be achieved for the large thyroid tumor case and when the presence of critical structures mitigated the contribution of additional fields. The calculation of the biologically optimized plans can be completed in a clinically viable time (<30 minutes) on a small 24-GPU system. CONCLUSIONS: By exploiting GPU acceleration, MC-based, biologically optimized plans were created for small-tumor target patients. This optimizer will be used in an upcoming feasibility trial on LETd painting for radioresistant tumors.

A GPU-accelerated and Monte Carlo-based intensity modulated proton therapy optimization system.

PURPOSE: Conventional spot scanning intensity modulated proton therapy (IMPT) treatment planning systems (TPSs) optimize proton spot weights based on analytical dose calculations. These analytical dose calculations have been shown to have severe limitations in heterogeneous materials. Monte Carlo (MC) methods do not have these limitations; however, MC-based systems have been of limited clinical use due to the large number of beam spots in IMPT and the extremely long calculation time of traditional MC techniques. In this work, the authors present a clinically applicable IMPT TPS that utilizes a very fast MC calculation. METHODS: An in-house graphics processing unit (GPU)-based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified least-squares optimization method was used to achieve the desired dose volume histograms (DVHs). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that resulted from maintaining the intrinsic CT resolution. The effects of tail cutoff and starting condition were studied and minimized in this work. RESULTS: For relatively large and complex three-field head and neck cases, i.e., >100,000 spots with a target volume of ∼ 1000 cm(3) and multiple surrounding critical structures, the optimization together with the initial MC dose influence map calculation was done in a clinically viable time frame (less than 30 min) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The in-house MC TPS plans were comparable to a commercial TPS plans based on DVH comparisons. CONCLUSIONS: A MC-based treatment planning system was developed. The treatment planning can be performed in a clinically viable time frame on a hardware system costing around 45,000 dollars. The fast calculation and optimization make the system easily expandable to robust and multicriteria optimization.

Conduction in charged PbSe nanocrystal films.

Conduction in thin films of PbSe nanocrystals doped by electrochemical gating has been studied. Charging the film, with either electrons or holes, increases the conductance by orders of magnitude. The electrons in the 1S(e) state of nanocrystals in these films have a mobility as high as 5.0 x 10(-3) cm(2) V(-1) s(-1). Electrons in the 1P(e) state were found to have a differential mobility up to 3-5 times greater than the electrons in the 1S(e) state, and a mobility minima was found corresponding to the complete filling of the 1S(e) state. The temperature and electric field dependence of conductance in the film, measured between 4.3 and 135 K, were both well described by a variable range hopping model.