arXiv subjects

Lixiang Guo

Publications and source records attributed to Lixiang Guo.

5 recordsLinked to original sources

arXiv2026

Dosimetric Quantification of a Commercial Dual-Tube kV X-Ray System for Preclinical FLASH Research

A kV dual tube system has been disseminated as a commercial research platform for preclinical FLASH radiotherapy (RT). Because the tubes are arranged in a parallel opposed geometry, both output symmetry and time resolved tube synchronization are critical for achieving sufficiently high dose rates (DR) and reproducible study results. We quantified tube output asymmetry observed in depth dose measurements as well as tube synchronization and evaluated their impact on FLASH studies. The dual-tube system defines dose per pulse as the combined single pulse output from both tubes, with DR given by dose per pulse/pulse length. 3D dose distributions were reconstructed from film measurements to assess the impact of output discrepancies. Pulse synchronization between tubes was characterized using a scintillator with 1 ms resolution. We showed >20% discrepancies in output at nominally equal mA/ms settings. After we compensated such discrepancy by decreasing the current of the tube with higher output, the inter tube output difference was reduced to <1%, restoring symmetrical depth dose. We further simulated an in vivo intestinal irradiation in which naive tube settings resulted in >22% of the organ volume receiving >102% of the prescribed dose, compared with <7% when output compensation was applied. We identified a 10.2 +/- 7.0ms synchronization jitter between tubes, which disproportionately impacts the DR at low dose-per-pulse settings, particularly relevant for fractionated studies. Corresponding quality assurance (QA) was designed to monitor tube synchronization over time. We quantified the dosimetric impact of asymmetric output and synchronization and demonstrated implications for preclinical studies. The proposed methodology and QA would mitigate and monitor these effects, ensuring study reproducibility.

physics.med-ph↗

arXiv2025

An image-guided high-precision research platform for ultra-high dose rate spinal cord toxicity studies

Objective: While FLASH radiotherapy is recognized for short-term normal tissue sparing, its durability in late-responding organs remains uncertain, limiting clinical adoption. With its clinical importance and steep dose-response, the spinal cord is an ideal model for evaluating FLASH effect on late toxicity. This work introduces a robust image-guided research platform for high-precision irradiation at both CONV and UHDR to enable FLASH late toxicity studies using a rat spinal cord model. Approach: A modified LINAC was employed to irradiate the C1-T2 rat spinal cord with 18 MeV UHDR and CONV beams. A custom rat immobilization device, a portable X-ray imaging system, and an ion-chamber-based UHDR output monitoring system were integrated to ensure accurate C1-T2 localization and precise dose delivery. A Monte Carlo (MC) dose engine was developed to provide accurate dosimetry and support interpretation of in vivo results. Scintillator measurements were performed within the spinal cord to verify MC results and the precision of our platform. Results: We achieved submillimeter C1-T2 setup accuracy and maintained submillimeter intrafraction motion. Ion chamber readings showed linear correlation with UHDR output. MC indicated uniform irradiation along the central ~13 mm cord. Our CONV beam exhibited distribution close to that of the UHDR beam, with difference <3%, isolating dose rate as the only variable. Scintillator-measured dose agreed with MC within 4%, confirming both MC accuracy and the platform's high-precision delivery. Significance: We developed the first comprehensive, image-guided preclinical platform for accurate UHDR and CONV irradiation to investigate FLASH-mitigated spinal cord toxicity in rats. This work thus establishes a robust foundation for systematic evaluation of the FLASH effect in late-responding organs and for determining clinical applicability of FLASH.

physics.med-ph↗

arXiv2025

Comprehensive characterization and validation of a fast-resolving (1000 Hz) plastic scintillator for ultra-high dose rate electron dosimetry

Background: The normal tissue sparing effect of ultra-high dose rate irradiation (>40 Gy/s, UHDR), as compared to conventional dose rate (CONV), has attracted significant research interest for FLASH radiotherapy (RT). Accurate, dose rate independent, fast-responding dosimeters capable of resolving the spatiotemporal characteristics of UHDR beams are urgently needed to facilitate FLASH research and support its clinical translation. Tissue-equivalent scintillators, with millimeter-level spatial resolution and millisecond-level temporal resolution, possess these required characteristics and show strong potential for use in UHDR dosimetry. Purpose: We investigated the performance of the HYPERSCINT RP-FLASH scintillator system at up to 1000 Hz sampling frequency (fs) for UHDR electron beam dosimetry. Methods: The scintillator was exposed to CONV and UHDR electron irradiation using a LINAC-based FLASH platform. Its spectral characteristics were delineated with a four-component calibration, followed by a signal-to-dose calibration using 18 MeV CONV electron beam. The dose linearity and dosimetric accuracy in response to CONV and UHDR irradiation at 1 and 1000 Hz fs were quantified against ion chamber and EBT-XD film measurements. The response of the scintillator system was investigated as a function of beam energy (6 and 18 MeV), field size (2x2 to 25x25 cm2), dose per pulse (DPP, 0.8 to 2.3 Gy/pulse), and pulse repetition frequency (PRF, 30 to 180 Hz). Relative signal sensitivity was quantified against accumulated dose to account for the scintillator's radiation degradation. Pulse-resolved dose measurements at 18 MeV UHDR, obtained using the scintillator with 1000 Hz fs for a train of 10 pulses at 180 Hz PRF, were validated with a PMT-fiber optic scattered radiation detector.

physics.med-ph↗

arXiv2024

Electron FLASH platform for pre-clinical research: LINAC modification, simplification of pulse control and dosimetry

Background: FLASH radiotherapy is a treatment regime that delivers therapeutic dose to tumors at an ultra-high dose rate while maintaining adequate normal tissue sparing. However, a comprehensive understanding of the underlying mechanisms, potential late toxicities, and optimal fractionation schemes is important for successful clinical translation. This has necessitated extensive pre-clinical investigations, leading several research institutions to initiate dedicated FLASH research programs. Purpose: This work describes a workflow for establishing an easily accessible electron FLASH (eFLASH) platform. The platform incorporates simplified pulse control, optimized dose rate delivery, and validated Monte Carlo (MC) dose engine for accurate in vivo dosimetry dedicated to FLASH pre-clinical studies. Methods: Adjustment of the automatic frequency control (AFC) module allowed us to optimize the LINAC pulse form to achieve a uniform dose rate. A MC model for the 6 MeV FLASH beam was commissioned to ensure accurate dose calculation necessary for reproducible in vivo studies. Results: Optimizing the AFC module enabled the generation of a uniform pulse form, ensuring consistent dose per pulse and a uniform dose rate throughout FLASH irradiation. The MC model closely agreed with film measurements. MC dose calculations indicated that 6 MeV FLASH is adequate to achieve a uniform dose distribution for mouse whole brain irradiation but may not be optimal for the spinal cord study. Conclusions: We present a novel workflow for establishing a LINAC-based eFLASH research platform, incorporating techniques for optimized dose rate delivery, a simplified pulse control system, and validated MC engine. This work provides researchers with valuable new approaches to facilitate the development of robust and accessible LINAC-based system for FLASH studies.

physics.med-ph↗

arXiv2022

Can depth-adaptive BERT perform better on binary classification tasks

In light of the success of transferring language models into NLP tasks, we ask whether the full BERT model is always the best and does it exist a simple but effective method to find the winning ticket in state-of-the-art deep neural networks without complex calculations. We construct a series of BERT-based models with different size and compare their predictions on 8 binary classification tasks. The results show there truly exist smaller sub-networks performing better than the full model. Then we present a further study and propose a simple method to shrink BERT appropriately before fine-tuning. Some extended experiments indicate that our method could save time and storage overhead extraordinarily with little even no accuracy loss.

cs.CL↗