Intra-fractional geometric and dose/volume metric variations of magnetic resonance imaging-guided stereotactic radiotherapy of prostate bed after radical prostatectomy.

Background and purpose: Magnetic Resonance Imaging (MRI)-guided Stereotactic body radiotherapy (SBRT) treatment to prostate bed after radical prostatectomy has garnered growing interests. The aim of this study is to evaluate intra-fractional anatomic and dose/volume metric variations for patients receiving this treatment. Materials and methods: Nineteen patients who received 30-34 Gy in 5 fractions on a 0.35T MR-Linac were included. Pre- and post-treatment MRIs were acquired for each fraction (total of 75 fractions). The Clinical Target Volume (CTV), bladder, rectum, and rectal wall were contoured on all images. Volumetric changes, Hausdorff distance, Mean Distance to Agreement (MDA), and Dice similarity coefficient (DSC) for each structure were calculated. Median value and Interquartile range (IQR) were recorded. Changes in target coverage and Organ at Risk (OAR) constraints were compared and evaluated using Wilcoxon rank sum tests at a significant level of 0.05. Results: Bladder had the largest volumetric changes, with a median volume increase of 48.9 % (IQR 28.9-76.8 %) and a median MDA of 5.1 mm (IQR 3.4-7.1 mm). Intra-fractional CTV volume remained stable with a median volume change of 1.2 % (0.0-4.8 %). DSC was 0.97 (IQR 0.94-0.99). For the dose/volume metrics, there were no statistically significant changes observed except for an increase in bladder hotspot and a decrease of bladder V32.5 Gy and mean dose. The CTV V95% changed from 99.9 % (IQR 98.8-100 %) to 99.6 % (IQR 93.9-100 %). Conclusion: Despite intra-fractional variations of OARs, CTV coverage remained stable during MRI-guided SBRT treatments for the prostate bed.

Nodule detection and generation on chest X-rays: NODE21 Challenge.

Pulmonary nodules may be an early manifestation of lung cancer, the leading cause of cancer-related deaths among both men and women. Numerous studies have established that deep learning methods can yield high-performance levels in the detection of lung nodules in chest X-rays. However, the lack of gold-standard public datasets slows down the progression of the research and prevents benchmarking of methods for this task. To address this, we organized a public research challenge, NODE21, aimed at the detection and generation of lung nodules in chest X-rays. While the detection track assesses state-of-the-art nodule detection systems, the generation track determines the utility of nodule generation algorithms to augment training data and hence improve the performance of the detection systems. This paper summarizes the results of the NODE21 challenge and performs extensive additional experiments to examine the impact of the synthetically generated nodule training images on the detection algorithm performance.

Robust treatment planning for small animal radio-neuromodulation using focused kV x-ray beams.

BACKGROUND: In preclinical radio-neuromodulation research, small animal experiments are pivotal for unraveling radiobiological mechanism, investigating prescription and planning techniques, and assessing treatment effects and toxicities. However, the target size inside a rat brain is typically in the order of sub-millimeters. The small target inside the visual cortex neural region in rat brain with a diameter of around 1 mm was focused in this work to observe the physiological change of this region. Delivering uniform doses to the small target while sparing health tissues is challenging. Focused kV x-ray technique based on modern x-ray polycapillary focusing lens is a promising modality for small animal radio-neuromodulation. PURPOSE: The current manual planning method could lead to sub-optimal plans, and the positioning uncertainties due to mechanical accuracy limitations, animal immobilization, and robotic arm motion are not considered. This work aims to design a robust inverse planning method to optimize the intensities of focused kV x-ray beams located in beam trajectories to irradiate small mm-sized targets in rat brains for radio-neuromodulation. METHODS: Focused kV x-ray beams were generated through polycapillary x-ray focusing lenses on achieving small (≤0.3 mm) focus perpendicular to the beam. The beam trajectories were manually designed in 3D space in scanning-while-rotating mode. Geant4 Monte Carlo (MC) simulation generated a dose calculation matrix for each focused kV x-ray beam located in beam trajectories. In the proposed robust inverse planning method, an objective function combining a voxel-wise stochastic programming approach and L1 norm regularization was established to overcome the positioning uncertainties and obtain a high-quality plan. The fast iterative shrinkage thresholding algorithm (FISTA) was utilized to solve the objective function and obtain the optimal intensities. Four cases were employed to validate the feasibility and effectiveness of the proposed method. The manual and non-robust inverse planning methods were also implemented for comparison. RESULTS: The proposed robust inverse planning method achieved superior dose homogeneity and higher robustness against positioning uncertainties. On average, the clinical target volume (CTV) homogeneity index (HI) of robust inverse plan improved to 13.3 from 22.9 in non-robust inverse plan and 53.8 in manual plan if positioning uncertainties were also present. The average bandwidth at D90 was reduced by 6.5 Gy in the robust inverse plan, compared to 9.6 Gy in non-robust inverse plan and 12.5 Gy in manual plan. The average bandwidth at D80 was reduced by 3.4 Gy in robust inverse plan, compared to 5.5 Gy in non-robust inverse plan and 8.5 Gy in manual plan. Moreover, the dose delivery time of manual plan was reduced by an average reduction of 54.7% with robust inverse plan and 29.0% with non-robust inverse plan. CONCLUSION: Compared to manual and non-robust inverse planning methods, the robust inverse planning method improved the dose homogeneity and delivery efficiency and was resistant to the uncertainties, which are crucial for radio-neuromodulation utilizing focused kV x-rays.

Deep match: A zero-shot framework for improved fiducial-free respiratory motion tracking.

BACKGROUND AND PURPOSE: Motion management is essential to reduce normal tissue exposure and maintain adequate tumor dose in lung stereotactic body radiation therapy (SBRT). Lung SBRT using an articulated robotic arm allows dynamic tracking during radiation dose delivery. Two stereoscopic X-ray tracking modes are available - fiducial-based and fiducial-free tracking. Although X-ray detection of implanted fiducials is robust, the implantation procedure is invasive and inapplicable to some patients and tumor locations. Fiducial-free tracking relies on tumor contrast, which challenges the existing tracking algorithms for small (e.g., <15 mm) and/or tumors obscured by overlapping anatomies. To markedly improve the performance of fiducial-free tracking, we proposed a deep learning-based template matching algorithm - Deep Match. METHOD: Deep Match consists of four self-definable stages - training-free feature extractor, similarity measurements for location proposal, local refinements, and uncertainty level prediction for constructing a more trustworthy and versatile pipeline. Deep Match was validated on a 10 (38 fractions; 2661 images) patient cohort whose lung tumor was trackable on one X-ray view, while the second view did not offer sufficient conspicuity for tumor tracking using existing methods. The patient cohort was stratified into subgroups based on tumor sizes (<10 mm, 10-15 mm, and >15 mm) and tumor locations (with/without thoracic anatomy overlapping). RESULTS: On X-ray views that conventional methods failed to track the lung tumor, Deep Match achieved robust performance as evidenced by >80 % 3 mm-Hit (detection within 3 mm superior/inferior margin from ground truth) for 70 % of patients and <3 mm superior/inferior distance (SID) ∼1 mm standard deviation for all the patients. CONCLUSION: Deep Match is a zero-shot learning network that explores the intrinsic neural network benefits without training on patient data. With Deep Match, fiducial-free tracking can be extended to more patients with small tumors and with tumors obscured by overlapping anatomy.

Hypoxia-informed RBE-weighted beam orientation optimization for intensity modulated proton therapy.

BACKGROUND: Variable relative biological effectiveness (RBE) models in treatment planning have been proposed to optimize the therapeutic ratio of proton therapy. It has been reported that proton RBE decreases with increasing tumor oxygen level, offering an opportunity to address hypoxia-related radioresistance with RBE-weighted optimization. PURPOSE: Here, we obtain a voxel-level estimation of partial oxygen pressure to weigh RBE values in a single biologically informed beam orientation optimization (BOO) algorithm. METHODS: Three glioblastoma patients with [18 F]-fluoromisonidazole (FMISO)-PET/CT images were selected from the institutional database. Oxygen values were derived from tracer uptake using a nonlinear least squares curve fitting. McNamara RBE, calculated from proton dose, was then weighed using oxygen enhancement ratios (OER) for each voxel and incorporated into the dose fidelity term of the BOO algorithm. The nonlinear optimization problem was solved using a split-Bregman approach, with FISTA as the solver. The proposed hypoxia informed RBE-weighted method (HypRBE) was compared to dose fidelity terms using the constant RBE of 1.1 (cRBE) and the normoxic McNamara RBE model (RegRBE). Tumor homogeneity index (HI), maximum biological dose (Dmax), and D95%, as well as OAR therapeutic index (TI = gEUDCTV /gEUDOAR ) were evaluated along with worst-case statistics after normalization to normal tissue isotoxicity. RESULTS: Compared to [cRBE, RegRBE], HypRBE increased tumor HI, Dmax, and D95% across all plans by on average [31.3%, 31.8%], [48.6%, 27.1%], and [50.4%, 23.8%], respectively. In the worst-case scenario, the parameters increase on average by [12.5%, 14.7%], [7.3%,-8.9%], and [22.3%, 2.1%]. Despite increased OAR Dmean and Dmax by [8.0%, 3.0%] and [13.1%, -0.1%], HypRBE increased average TI by [22.0%, 21.1%]. Worst-case OAR Dmean, Dmax, and TI worsened by [17.9%, 4.3%], [24.5%, -1.2%], and [9.6%, 10.5%], but in the best cases, HypRBE escalates tumor coverage significantly without compromising OAR dose, increasing the therapeutic ratio. CONCLUSIONS: We have developed an optimization algorithm whose dose fidelity term accounts for hypoxia-informed RBE values. We have shown that HypRBE selects bE:\Alok\aaeams better suited to deliver high physical dose to low RBE, hypoxic tumor regions while sparing the radiosensitive normal tissue.

Minimum reporting standards should be expected for preclinical radiobiology irradiators and dosimetry in the published literature.

The cornerstones of science advancement are rigor in performing scientific research, reproducibility of research findings and unbiased reporting of design and results of the experiments. For radiation research, this requires rigor in describing experimental details as well as the irradiation protocols for accurate, precise and reproducible dosimetry. Most institutions conducting radiation biology research in in vitro or animal models do not have describe experimental irradiation protocols in sufficient details to allow for balanced review of their publication nor for other investigators to replicate published experiments. The need to increase and improve dosimetry standards, traceability to National Institute of Standards and Technology (NIST) standard beamlines, and to provide dosimetry harmonization within the radiation biology community has been noted for over a decade both within the United States and France. To address this requirement subject matter experts have outlined minimum reporting standards that should be included in published literature for preclinical irradiators and dosimetry.

Dosimetric predictors for genitourinary toxicity in MR-guided stereotactic body radiation therapy (SBRT): Substructure with fraction-wise analysis.

BACKGROUND: MR-guided radiation therapy (MRgRT) systems provide superior soft tissue contrast than x-ray based systems and can acquire real-time cine for treatment gating. These features allow treatment planning margins to be reduced, allowing for improved critical structure sparing and reduced treatment toxicity. Despite this improvement, genitourinary (GU) toxicity continues to affect many patients. PURPOSE: (1) To identify dosimetric predictors, potentially in combination with clinical parameters, of GU toxicity following SBRT by leveraging MRgRT to accurately monitor daily dose, beyond predicted dose calculated during planning. (2) Improve awareness of toxicity-sensitive bladder substructures, specifically the trigone and urethra. METHODS: Sixty-nine prostate cancer patients (NCT04384770 clinical trial) were treated on a ViewRay MRIdian MRgRT system, with 40 Gy prescribed to 95% of the PTV in over five fractions. Overall, 17 (24.6%) prostate patients reported acute grade 2 GU toxicity. The CTV, PTV, bladder, bladder wall, trigone, urethra, rectum, and rectal wall were contoured on the planning and daily treatment MRIs. Planning and daily treatment DVHs (0.1 Gy increments), organ doses (min, max, mean), and organ volumes were recorded. Daily dose was estimated by transferring the planning dose distributions to the daily MRI based on the daily setup alignment. Patients were partitioned into a training (55) and testing set (14). Dose features were pre-filtered using a t-test followed by maximum relevance minimum redundancy (MRMR) algorithm. Logistic regression was investigated with regularization to select dosimetric predictors. Specifically, two approaches: time-group least absolute shrinkage and selection (LASSO), and interactive grouped greedy algorithm (IGA) were investigated. Shared features across the planning and five treatment fractions were grouped to encourage consistency and stability. The conventional flat non-temporally grouped LASSO was also evaluated to provide a solid benchmark. After feature selection, a final logistic regression model was trained. Dosimetric regression models were compared to a clinical regression model with only clinical parameters (age, baseline IPSS, prostate gland size, ADT usage, etc.) and a hybrid model, combining the best performing dosimetric features with the clinical parameters, was evaluated. Final model performance was evaluated on the testing set using accuracy, sensitivity, and specificity determined by the optimal threshold of the training set. RESULTS: IGA had the best testing performance with an accuracy/sensitivity/specificity of 0.79/0.67/0.82, selecting 12 groups covering the bladder (V19.8 Gy, V20.5 Gy), bladder wall (19.7 Gy), trigone (15.9, 18.2, 43.3 Gy), urethra (V41.4 Gy, V41.7 Gy), CTV (V41.9 Gy), rectum (V8.5 Gy), and rectal wall (1.2, 44.1 Gy) dose features. Absolute bladder V19.8 Gy and V20.5 Gy were the most important features, followed by relative trigone 15.9  and 18.2 Gy. Inclusion of clinical parameters in the hybrid model with IGA did not significantly change regression performance. CONCLUSION: Overall, IGA feature selection resulted in the best GU toxicity prediction performance. This exploratory study demonstrated the feasibility of identification and analysis of dosimetric toxicity predictors with awareness to sensitive substructures and daily dose to potentially provide consistent and stable dosimetric metrics to guide treatment planning. Further patient accruement is warranted to further assess dosimetric predictor and perform validation.

Impact of Interfractional Bladder and Trigone Displacement and Deformation on Radiation Exposure and Subsequent Acute Genitourinary Toxicity: A Post Hoc Analysis of Patients Treated with Magnetic Resonance Imaging-Guided Prostate Stereotactic Body Radiation Therapy in a Phase 3 Randomized Trial.

PURPOSE: Emerging data suggest that trigone dosimetry may be more associated with poststereotactic body radiation therapy (SBRT) urinary toxicity than whole bladder dosimetry. We quantify the dosimetric effect of interfractional displacement and deformation of the whole bladder and trigone during prostate SBRT using on-board, pretreatment 0.35T magnetic resonance images (MRI). METHODS AND MATERIALS: Seventy-seven patients treated with MRI-guided prostate SBRT (40 Gy/5 fractions) on the MRI arm of a phase 3 single-center randomized trial were included. Bladder and trigone structures were contoured on images obtained from a 0.35T simulation MRI and 5 on-board pretreatment MRIs. Dice similarity coefficient (DSC) scores and changes in volume between simulation and daily treatments were calculated. Dosimetric parameters including Dmax, D0.03 cc, Dmean, V40 Gy, V39 Gy, V38 Gy, and V20 Gy for the bladder and trigone for the simulation and daily treatments were collected. Both physician-scored (Common Terminology Criteria for Adverse Events, version 4.03 scale) as well as patient-reported (International Prostate Symptom Scores and the Expanded Prostate Cancer Index Composite-26 scores) acute genitourinary (GU) toxicity outcomes were collected and analyzed. RESULTS: The average treatment bladder volume was about 30% smaller than the simulation bladder volume; however, the trigone volume remained fairly consistent despite being positively correlated with total bladder volume. Overall, the trigone accounted for <2% of the bladder volume. Median DSC for the bladder was 0.79, whereas the median DSC of the trigone was only 0.33. No statistically significant associations between our selected bladder and trigonal dosimetric parameters and grade ≥2 GU toxicity were identified, although numerically, patients with GU toxicity (grade ≥2) had higher intermediate doses to the bladder (V20 Gy and Dmean) and larger volumes exposed to higher doses in the trigone (V40 Gy, V39 Gy, and V38 Gy). CONCLUSIONS: The trigone exhibits little volume change, but considerable interfractional displacement/deformation. As a result, the relative volume of the trigone receiving high doses during prostate SBRT varies substantially between fractions, which could influence GU toxicity and may not be predicted by radiation planning dosimetry.

[Effects of allicin on insulin resistance and free fatty acid levels in obese rats with periodontitis].

PURPOSE: To explore the effects of allicin on insulin resistance and free fatty acids (FFAs) levels in obese rats with periodontitis. METHODS: Forty rats were randomly divided into healthy group, periodontitis group, and low, medium and high dose groups, with 8 rats in each group. The healthy group was healthy rats, and the other groups were induced by sodium glutamate(MSG). After successfully establishing an obesity model, the maxillary molars were ligated and smeared to establish a periodontitis model. Both the periodontitis group and the healthy group were given normal saline, and the allicin low, medium and high dose groups were given allicin 20，40 and 60 mg·kg-1·d-1, mixed with feed for oral administration. After 21 days of treatment, the fasting blood glucose(FPG), fasting insulin (FINS), insulin resistance index (HOMA-IR) scores and FFAs levels of the homeostatic model in rats were detected. The protein expression of TLR4/MyD88 signaling pathway were compared. Statistical analysis was performed with SPSS 22.0 software package. RESULTS: Compared with the healthy group, FPG, FINS levels, HOMA-IR, IL-6 and TNF-α levels of the periodontitis group were significantly increased, and the expression of TLR4 and MyD88 proteins was significantly increased(P＜0.05). Compared with the periodontitis group, FPG, FINS levels, HOMA-IR, IL-6 and TNF-α levels of low, medium and high-doses groups were significantly decreased, and the expression of TLR4 and MyD88 proteins was significantly decreased (P＜0.05). Compared with the low-dose group, the levels of FPG and FINS, HOMA-IR, IL-6 and TNF-α levels of the middle and high-dose groups were significantly decreased, and the expression of TLR4 and MyD88 proteins was significantly decreased (P＜0.05). Compared with the middle-dose group, the levels of FPG and FINS, HOMA-IR, IL-6 and TNF-α levels of the high-dose group were significantly decreased, and the expression of TLR4 and MyD88 proteins was significantly decreased (P＜0.05). After treatment, FFAs of the low, medium and high-dose groups were significantly lower than those before treatment(P＜0.05). Compared with the healthy group, FFAs levels of the periodontitis group, low-dose and medium-dose groups were significantly increased. Compared with the periodontitis group, FFAs levels of the low, medium and high-dose groups were significantly increased. Compared with the low-dose group, FFAs levels of the high-dose group were significantly increased. Compared with the middle-dose group, FFAs levels of the high-dose group were significantly increased (P＜0.05). CONCLUSIONS: Allicin can improve insulin resistance and obesity in obese rats with periodontitis, and its mechanism of action is related to the TLR4/MyD88 signaling pathway.

First platelet transfusion refractoriness in a patient with acute myelocytic leukemia: A case report.

BACKGROUND: Platelet transfusion is of great significance in the treatment of thrombocytopenia caused by myelosuppression during intensive chemotherapy in patients with acute leukemia. In recent years, with platelet transfusion increasing, ineffective platelet transfusion has become increasingly prominent. Generally speaking, platelet antibodies can be produced after repeated transfusion, thus rendering subsequent platelet transfusion ineffective. We report a case of first platelet transfusion refractoriness (PTR) in a patient with acute myelocytic leukemia (AML). Due to the rarity of such cases in clinical practice, there have been no relevant case reports so far. CASE SUMMARY: A 51-year-old female patient attended the hospital due to throat pain and abnormal blood cells for 4 d. Her diagnosis was acute myelocytic leukemia [M2 type Fms related receptor tyrosine kinase 3, Isocitrate Dehydrogenase 1, Nucleophosmin 1, Neuroblastoma RAS viral oncogene homolog (+) high-risk group]. She was treated with "IA" (IDA 10 mg day 1-3 and Ara-C 0.2 g day 1-5) chemotherapy. When her condition improved, the patient was discharged from the hospital, instructed to take medicine as prescribed by the doctor after discharge, and returned to the hospital for further chemotherapy on time. CONCLUSION: We report a rare case of first platelet transfusion failure in a patient with AML during induction chemotherapy, which may be related to the production of platelet antibodies induced by antibiotics and excessive tumor load. This also suggests that we should consider the influence of antibiotics when the rare situation of first platelet transfusion failure occurs in patients with AML. When platelet antibodies are produced, immunoglobulins can be used to block antibodies, thereby reducing platelet destruction. For patients with PTR, both immune and non-immune factors need to be considered and combined in clinical practice along with individualized treatment to effectively solve the problem.

First report of bacterial leaf spot on Hami melon caused by Pseudomonas aeruginosa in China.

Hami melon (Cucumis melon var. saccharinus) is an economically important crop all over the world. It is being extensively planted in greenhouse in the southwest part of Hainan province, China. A new bacterial leaf spot was observed in a 20 hm2 Hami melon plantation in Huangliu town, Ledong county, Hainan province, in January 2022. The incidence of the disease was approximately 5%. Symptoms were irregularly shaped, brown lesions with yellow haloes on mature leaves, and first appeared as small, dark-green, water-soaking spots. Specimens from the lesion margin were disinfected by submersion in 0.1% mercuric chloride for 1 min, then soaked with 75% alcohol for 30 s, and rinsed with sterilized distilled water. The tissues were then ground in 2 ml of sterile water and allowed to stand for 5min. The supernatant was streaked onto nutrient agar (NA) and incubated for 48h at 30°C. Colonies were round, smooth, colorless, nearly transparent, bead-shaped at first, and then became lightly blue. After being cultured for days on NA at 30℃, the bacteria can turn the media brown. Yellow green pigments (pyoverdin) that fluoresce under ultraviolet light could be produced by the isolates in the Luria Broth. The bacteria were gram-negative, rod shaped with a single polar flagellum, 0.4 to 1.1 × 1.4 to 3.4 µm. Its physiological and biochemical characteristics were as follows: positive for the oxidase, aerobic, arginine dihydrolase, gelatin liquefaction, denitrification, lipase, growth at 41℃, utilization of mannitol, and production of pyocyanin tests; negative for the hydrolysis of starch, levan formation, lecithinase, growth at 4℃, growth in media supplemented with 8.5% NaCl, and utilization of maltose, xylose, and ethylene glycol tests. The 16S rRNA (1,437 bp), gyrB (1,181 bp), and rpoB genes (1,510 bp) were amplified with 27F/1492R (Zhang et al. 2016）, UP-1s/UP-2sr（Hannula M，2007）, and rpoB-F/rpoB-R (Ogier, JC. et al., 2019) primer sets respectively. One of the 5 isolates collected was sequenced. A BLASTn search of GenBank revealed that the sequence of 16S rRNA gene (OQ918303) had 99.7% identity and 98% coverage comparing with the best hit Pseudomonas aeruginosa strain DSM 50071(NR_117678.1), and both gyrB (OR261077) and rpoB (OR261078) had 99.9% identity and over 98% coverage comparing with P. aeruginosa E90 (CP044006.1). A pathogenicity test was conducted by spraying a suspension of the bacteria (108 CFU/mL) onto 10 Hami melon seedlings with two true leaves. Controls were inoculated with sterile water. All inoculated plants were maintained at 28℃ with 80 to 85% relative humidity in a greenhouse. Dark-green, water soaking spots appeared on the cotyledon and stems of treated seedlings 3-5 days after inoculation, and dark green lesions with halos were observed on the true leaves at the same time. Symptoms did not occur on the control plants. The bacteria which were re-isolated from the inoculated plants were confirmed as P. aeruginosa based on the 16S rRNA gene sequence. The bacterium was not isolated from control plants. P. aeruginosa has been reported to cause disease on a variety of plants including tomato (Zhang et al., 2021), poplar (Liu, et al., 2019), ginseng (Gao et al., 2014), tinda (Mondal et al., 2012), onion (Abd-Alla et al., 2011), tobacco (Yu et al., 2008) and sweet basil (Walker et al., 2004). As far as we know, this is the first report of P. aeruginosa causing leaf spot on Hami melon in China.. This report will contribute to the recognition and diagnosis of the new disease for the Hami melon growers.

A unified path seeking algorithm for IMRT and IMPT beam orientation optimization.

Objective. Fully automated beam orientation optimization (BOO) for intensity-modulated radiotherapy and intensity modulated proton therapy (IMPT) is gaining interest, since achieving optimal plan quality for an unknown number of fixed beam arrangements is tedious. Fast group sparsity-based optimization methods have been proposed to find the optimal orientation, but manual tuning is required to eliminate the exact number of beams from a large candidate set. Here, we introduce a fast, automated gradient descent-based path-seeking algorithm (PathGD), which performs fluence map optimization for sequentially added beams, to visualize the dosimetric benefit of one added field at a time.Approach. Several configurations of 2-4 proton and 5-15 photon beams were selected for three head-and-neck patients using PathGD, which was compared to group sparsity-regularized BOO solved with the fast iterative shrinkage-thresholding algorithm (GS-FISTA), and manually selected IMPT beams or one coplanar photon VMAT arc (MAN). Once beams were chosen, all plans were compared on computational efficiency, dosimetry, and for proton plans, robustness.Main results. With each added proton beam, Clinical Target Volume (CTV) and organs at risk (OAR) dosimetric cost improved on average across plans by [1.1%, 13.6%], and for photons, [0.6%, 2.0%]. Comparing algorithms, beam selection for PathGD was faster than GS-FISTA on average by 35%, and PathGD matched the CTV coverage of GS-FISTA plans while reducing OAR mean and maximum dose in all structures by an average of 13.6%. PathGD was able to improve CTV [Dmax, D95%] by [2.6%, 5.2%] and reduced worst-case [max, mean] dose in OARs by [11.1%, 13.1%].Significance. The benefit of a path-seeking algorithm is the beam-by-beam analysis of dosimetric cost. PathGD was shown to be most efficient and dosimetrically desirable amongst group sparsity and manual BOO methods, and highlights the sensitivity of beam addition for IMPT in particular.

Analytical HDR prostate brachytherapy planning with automatic catheter and isotope selection.

BACKGROUND: High dose rate (HDR) brachytherapy is commonly used to treat prostate cancer. Existing HDR planning systems solve the dwell time problem for predetermined catheters and a single energy source. PURPOSE: Additional degrees of freedom can be obtained by relaxing the catheters' pre-designation and introducing more source types, and may have a dosimetric benefit, particularly in improving conformality to spare the urethra. This study presents a novel analytical approach to solving the corresponding HDR planning problem. METHODS: The catheter and dual-energy source selection problem was formulated as a constrained optimization problem with a non-convex group sparsity regularization. The optimization problem was solved using the fast-iterative shrinkage-thresholding algorithm (FISTA). Two isotopes were considered. The dose rates for the HDR 4140 Ytterbium (Yb-169) source and the Elekta Iridium (Ir-192) HDR Flexisource were modeled according to the TG-43U1 formalism and benchmarked accordingly. Twenty-two retrospective HDR prostate brachytherapy patients treated with Ir-192 were considered. An Ir-192 only (IRO), Yb-169 only (YBO), and dual-source (DS) plan with optimized catheter location was created for each patient with N catheters, where N is the number of catheters used in the clinically delivered plans. The DS plans jointly optimized Yb-169 and Ir-192 dwell times. All plans and the clinical plans were normalized to deliver a 15 Gy prescription (Rx) dose to 95% of the clinical treatment volume (CTV) and evaluated for the CTV D90%, V150%, and V200%, urethra D0.1cc and D1cc, bladder V75%, and rectum V75%. Dose-volume histograms (DVHs) were generated for each structure. RESULTS: The DS plans ubiquitously selected Ir-192 as the only treatment source. IRO outperformed YBO in organ at risk (OARs) OAR sparing, reducing the urethra D0.1cc and D1cc by 0.98% ( p = 2.22 ∗ 10 - 9 $p\ = \ 2.22*{10^{ - 9}}$ ) and 1.09% ( p = 1.22 ∗ 10 - 10 $p\ = \ 1.22*{10^{ - 10}}$ ) of the Rx dose, respectively, and reducing the bladder and rectum V75% by 0.09 ( p = 0.0023 $p\ = \ 0.0023$ ) and 0.13 cubic centimeters (cc) ( p = 0.033 $p\ = \ 0.033$ ), respectively. The YBO plans delivered a more homogenous dose to the CTV, with a smaller V150% and V200% by 3.20 ( p = 4.67 ∗ 10 - 10 $p\ = \ 4.67*{10^{ - 10}}$ ) and 1.91 cc ( p = 5.79 ∗ 10 - 10 $p\ = \ 5.79*{10^{ - 10}}$ ), respectively, and a lower CTV D90% by 0.49% ( p = 0.0056 $p\ = \ 0.0056$ ) of the prescription dose. The IRO plans reduce the urethral D1cc by 2.82% ( p = 1.38 ∗ 10 - 4 $p\ = \ 1.38*{10^{ - 4}}$ ) of the Rx dose compared to the clinical plans, at the cost of increased bladder and rectal V75% by 0.57 ( p = 0.0022 $p\ = \ 0.0022$ ) and 0.21 cc ( p = 0.019 $p\ = \ 0.019$ ), respectively, and increased CTV V150% by a mean of 1.46 cc ( p = 0.010 $p\ = \ 0.010$ ) and CTV D90% by an average of 1.40% of the Rx dose ( p = 8.80 ∗ 10 - 8 $p\ = \ 8.80*{10^{ - 8}}$ ). While these differences are statistically significant, the clinical differences between the plans are minimal. CONCLUSIONS: The proposed analytical HDR planning algorithm integrates catheter and isotope selection with dwell time optimization for varying clinical goals, including urethra sparing. The planning method can guide HDR implants and identify promising isotopes for specific HDR clinical goals, such as target conformality or OAR sparing.

Contrast-Enhanced Liver Magnetic Resonance Image Synthesis Using Gradient Regularized Multi-Modal Multi-Discrimination Sparse Attention Fusion GAN.

PURPOSES: To provide abdominal contrast-enhanced MR image synthesis, we developed an gradient regularized multi-modal multi-discrimination sparse attention fusion generative adversarial network (GRMM-GAN) to avoid repeated contrast injections to patients and facilitate adaptive monitoring. METHODS: With IRB approval, 165 abdominal MR studies from 61 liver cancer patients were retrospectively solicited from our institutional database. Each study included T2, T1 pre-contrast (T1pre), and T1 contrast-enhanced (T1ce) images. The GRMM-GAN synthesis pipeline consists of a sparse attention fusion network, an image gradient regularizer (GR), and a generative adversarial network with multi-discrimination. The studies were randomly divided into 115 for training, 20 for validation, and 30 for testing. The two pre-contrast MR modalities, T2 and T1pre images, were adopted as inputs in the training phase. The T1ce image at the portal venous phase was used as an output. The synthesized T1ce images were compared with the ground truth T1ce images. The evaluation metrics include peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and mean squared error (MSE). A Turing test and experts' contours evaluated the image synthesis quality. RESULTS: The proposed GRMM-GAN model achieved a PSNR of 28.56, an SSIM of 0.869, and an MSE of 83.27. The proposed model showed statistically significant improvements in all metrics tested with p-values < 0.05 over the state-of-the-art model comparisons. The average Turing test score was 52.33%, which is close to random guessing, supporting the model's effectiveness for clinical application. In the tumor-specific region analysis, the average tumor contrast-to-noise ratio (CNR) of the synthesized MR images was not statistically significant from the real MR images. The average DICE from real vs. synthetic images was 0.90 compared to the inter-operator DICE of 0.91. CONCLUSION: We demonstrated the function of a novel multi-modal MR image synthesis neural network GRMM-GAN for T1ce MR synthesis based on pre-contrast T1 and T2 MR images. GRMM-GAN shows promise for avoiding repeated contrast injections during radiation therapy treatment.

Gell: A GPU-powered 3D hybrid simulator for large-scale multicellular system.

As a powerful but computationally intensive method, hybrid computational models study the dynamics of multicellular systems by evolving discrete cells in reacting and diffusing extracellular microenvironments. As the scale and complexity of studied biological systems continuously increase, the exploding computational cost starts to limit large-scale cell-based simulations. To facilitate the large-scale hybrid computational simulation and make it feasible on easily accessible computational devices, we develop Gell (GPU Cell), a fast and memory-efficient open-source GPU-based hybrid computational modeling platform for large-scale system modeling. We fully parallelize the simulations on GPU for high computational efficiency and propose a novel voxel sorting method to further accelerate the modeling of massive cell-cell mechanical interaction with negligible additional memory footprint. As a result, Gell efficiently handles simulations involving tens of millions of cells on a personal computer. We compare the performance of Gell with a state-of-the-art paralleled CPU-based simulator on a hanging droplet spheroid growth task and further demonstrate Gell with a ductal carcinoma in situ (DCIS) simulation. Gell affords ~150X acceleration over the paralleled CPU method with one-tenth of the memory requirement.

Technical note: Multi-MATE, a high-throughput platform for automated image-guided small-animal irradiation.

BACKGROUND: Small animal irradiation is essential to study the radiation response of new interventions before or parallel to human therapy. Image-guided radiotherapy (IGRT) and intensity-modulated radiotherapy (IMRT) are recently adopted in small animal irradiation to more closely mimic human treatments. However, sophisticated techniques require exceedingly high time, resources, and expertize that are often impractical. PURPOSE: We propose a high throughput and high precision platform named Multiple Mouse Automated Treatment Environment (Multi-MATE) to streamline image-guided small animal irradiation. METHODS: Multi-MATE consists of six parallel and hexagonally arranged channels, each equipped with a transfer railing, a 3D-printed immobilization pod, and an electromagnetic control unit, computer-controlled via an Arduino interface. The mouse immobilization pods are transferred along the railings between the home position outside the radiation field and the imaging/irradiation position at the irradiator isocenter. All six immobilization pods are transferred to the isocenter in the proposed workflow for parallel CBCT scans and treatment planning. The immobilization pods are then sequentially transported to the imaging/therapy position for dose delivery. The positioning reproducibility of Multi-MATE are evaluated using CBCT and radiochromic films. RESULTS: While parallelizing and automating the image-guided small animal radiation delivery, Multi-MATE achieved the average pod position reproducibility of 0.17 ± 0.04 mm in the superior-inferior direction, 0.20 ± 0.04 mm in the left-right direction, and 0.12 ± 0.02mm in the anterior-posterior direction in repeated CBCT tests. Additionally, in image-guided dose delivery tasks, Multi-MATE demonstrated the positioning reproducibility of 0.17 ± 0.06 mm in the superior-inferior direction, 0.19 ± 0.06 mm in the left-right direction. CONCLUSIONS: We designed, fabricated, and tested a novel automated irradiation platform, Multi-MATE to accelerate and automate image-guided small animal irradiation. The automated platform minimizes human operation and achieves high setup reproducibility and image-guided dose delivery accuracy. Multi-MATE thus removes a major barrier to implementing high-precision preclinical radiation research.

An Efficient and Robust Method for Chest X-ray Rib Suppression That Improves Pulmonary Abnormality Diagnosis.

BACKGROUND: Suppression of thoracic bone shadows on chest X-rays (CXRs) can improve the diagnosis of pulmonary disease. Previous approaches can be categorized as either unsupervised physical models or supervised deep learning models. Physical models can remove the entire ribcage and preserve the morphological lung details but are impractical due to the extremely long processing time. Machine learning (ML) methods are computationally efficient but are limited by the available ground truth (GT) for effective and robust training, resulting in suboptimal results. PURPOSE: To improve bone shadow suppression, we propose a generalizable yet efficient workflow for CXR rib suppression by combining physical and ML methods. MATERIALS AND METHOD: Our pipeline consists of two stages: (1) pair generation with GT bone shadows eliminated by a physical model in spatially transformed gradient fields; and (2) a fully supervised image denoising network trained on stage-one datasets for fast rib removal from incoming CXRs. For stage two, we designed a densely connected network called SADXNet, combined with a peak signal-to-noise ratio and a multi-scale structure similarity index measure as the loss function to suppress the bony structures. SADXNet organizes the spatial filters in a U shape and preserves the feature map dimension throughout the network flow. RESULTS: Visually, SADXNet can suppress the rib edges near the lung wall/vertebra without compromising the vessel/abnormality conspicuity. Quantitively, it achieves an RMSE of ~0 compared with the physical model generated GTs, during testing with one prediction in <1 s. Downstream tasks, including lung nodule detection as well as common lung disease classification and localization, are used to provide task-specific evaluations of our rib suppression mechanism. We observed a 3.23% and 6.62% AUC increase, as well as 203 (1273 to 1070) and 385 (3029 to 2644) absolute false positive decreases for lung nodule detection and common lung disease localization, respectively. CONCLUSION: Through learning from image pairs generated from the physical model, the proposed SADXNet can make a robust sub-second prediction without losing fidelity. Quantitative outcomes from downstream validation further underpin the superiority of SADXNet and the training ML-based rib suppression approaches from the physical model yielded dataset. The training images and SADXNet are provided in the manuscript.

An endophytic fungus Schizophyllum commune isolated from Panax ginseng enhances hairy roots growth and ginsenoside biosynthesis.

Using endophytic fungal elicitors to increase the accumulation of valuable secondary metabolites in plant tissue culture is an effective biotechnology strategy. In this study, a collection of 56 strains of endophytic fungi were isolated from different organs of cultivated Panax ginseng, of which seven strains can be symbiotically co-cultured with the hairy roots of P. ginseng. Further experiments observed that strain 3R-2, identified as endophytic fungus Schizophyllum commune, can not only infect hairy roots but also promote the accumulation of specific ginsenosides. This was further verified because S. commune colonization significantly affected the overall metabolic profile of ginseng hairy roots. By comparing the effects of S. commune mycelia and its mycelia extract (EM) on ginsenoside production in P. ginseng hairy roots, the EM was confirmed to be a relatively better stimulus elicitor. Additionally, the introduction of EM elicitor can significantly enhance the expressions of key enzyme genes of pgHMGR, pgSS, pgSE, and pgSD involved in the biosynthetic pathway of ginsenosides, which was deemed the most relevant factor for promoting ginsenosides production during the elicitation period. In conclusion, this study is the first to show that the EM of endophytic fungus S. commune can be considered as an effective endophytic fungal elicitor for increasing the biosynthesis of ginsenosides in hairy root cultures of P. ginseng.

The protective roles of liraglutide on Kawasaki disease via AMPK/mTOR/NF-κB pathway.

Kawasaki disease (KD) is an acute febrile rash illness among children of unknown etiology, with coronary artery injury. The main purpose of this study was to investigate the protective effects of liraglutide on KD, and elucidate the underlying mechanisms. The candida albicans water-soluble fraction (CAWS)-induced coronary arteritis of mouse KD model in vivo and tumor necrosis factor α (TNF-α) induced endothelial cell injury of human umbilical vein endothelial cell (HUVEC) model in vitro were used to explore the anti-inflammation and anti-apoptosis effects of liraglutide on KD. In vivo results showed that liraglutide could significantly alleviate the coronary artery injury of KD mice, as evidenced by the reduction of inflammatory infiltration around the coronary arteries, downregulation of inflammatory cytokines and chemokines expressions, and decrease of TUNEL (Terminal deoxynucleotidyl transferase dUTP nick end labeling) positive cell rates. The results in vitro also displayed that liraglutide could markedly relieve the inflammatory of TNF-α induced HUVECs through downregulating the expressions of inflammatory and chemokine indicators as well as inhibit TNF-α induced HUVEC apoptosis by the less ratio of apoptotic cells, the more loss of mitochondrial membrane potential (△Ψm), the lower level of intracellular reactive oxygen species (ROS), and the more ratio of BCL-2/BAX. Further in vivo and in vitro studies demonstrated that liraglutide could rescue endothelial cell injury through AMPK/mTOR/NF-κB pathway. In conclusion, liraglutide could play protective roles on KD through inhibiting endothelial cell inflammation and apoptosis via the activation of AMPK/mTOR/NF-κB pathway.