Biomedical subjects

Lei Xing

Publications and source records attributed to Lei Xing.

17 recordsLinked to original sources

PubMed2026

Leveraging Interradiomic Feature Relationships for Enhanced Prediction of Distant Metastasis and Characterization of Heterogeneity in Head and Neck Cancer.

PURPOSE: Distant metastasis remains a major cause of treatment failure in head and neck (HN) cancer, highlighting the need for more accurate early risk stratification. This study developed and validated a deep radiomics framework to characterize tumor heterogeneity from pretreatment computed tomography (CT) images and improve prediction of distant metastasis-free survival (DMFS). METHODS AND MATERIALS: This multicenter study included 3421 patients with HN cancer from 4 cohorts across 12 institutions. Radiomics features were extracted from primary tumors and transformed into OmicsMaps, a structured representation that spatially organizes interfeature relationships to facilitate learning of complex prognostic patterns. A convolutional neural network was trained to derive prognostic signatures, which were integrated with key clinical variables to construct an OmicsMap-clinical fusion model for patient risk stratification. Model performance was assessed using the concordance index (C-index) and time-dependent area under the receiver operating characteristic curve (AUC) in the CT Images from Large Head and Neck Cohort (RADCURE), HEAD-NECK-RADIOMICS-HN1 (HN1), and Head-Neck-Positron Emission Tomography-Computed Tomography (HN-PET-CT) cohorts. Radiogenomic analyses using RNA-seq data were conducted in the Cancer Genome Atlas Head-Neck Squamous Cell Carcinoma (TCGA-HNSC) cohort to investigate biological characteristics associated with the imaging-defined risk groups. RESULTS: The OmicsMap achieved C-index values of 0.742, 0.768, and 0.671 in the RADCURE, HN1, and HN-PET-CT cohorts, outperforming the conventional radiomics approach by 5.40%-6.37%. Incorporating clinical variables further improved generalizability, yielding a C-index of 0.864 (HN1) and 0.730 (HN-PET-CT), with time-dependent AUC of 0.727-0.895. The fusion model consistently stratified patients into distinct high- and low-risk groups for both DMFS and overall survival across cohorts (P <.01). Radiogenomic analyses revealed enrichment of immune-related pathways in the low-risk group, whereas the high-risk group exhibited a more aggressive phenotype enriched for proliferation, hypoxia, and epithelial-mesenchymal transition pathways, along with a fibrosis-prone tumor microenvironment characterized by extracellular matrix remodeling. CONCLUSIONS: Modeling interradiomic feature relationships using the OmicsMap representation substantially improves CT-based prediction of DMFS and characterization of tumor heterogeneity in HN cancer, supporting precision risk stratification in clinical oncology.

Journal Article↗

PubMed2026

Perturbation of genes linked to common schizophrenia risk variants identifies cilia programs.

Schizophrenia (SCZ) is a common psychiatric disorder characterized by psychosis, emotional withdrawal, and cognitive deficits. Most SCZ risk variants reside in non-coding regions of the genome and are thought to influence disease risk by modulating gene regulation. However, the target genes, biological pathways, and cell types through which these variants exert their effects remain poorly understood. To address this gap, we employed in vivo CRISPR droplet sequencing (CROP-seq) in the postnatal mouse neocortex. We perturbed 12 SCZ risk genes previously linked to functionally validated risk variants, followed by single-cell RNA sequencing. We identified 3,031 differentially expressed genes (DEGs) that recapitulate transcriptional alterations observed in postmortem SCZ brains. Integrative analysis using DEG clustering, factor analysis, and gene regulatory network inference uncovered convergent gene programs with distinct biological functions and cell type specificity. Notably, ciliary transcriptional programs consistently emerged across analytical frameworks. The primary cilium is a neurocircuit modulating signaling organelle in neurons and glia that remains understudied in SCZ. Perturbation of key contributors to the ciliary transcriptional programs led to significant alterations in ciliary structure, suggesting that SCZ genetic risk factors may influence how brain cells sense and transduce extracellular signals through synapse-independent mechanisms. Together, this study provides the first in vivo characterization of the functional consequence of common variant architecture in SCZ and implicates ciliary dysfunction as a convergent downstream mechanism.

Journal Article↗

PubMed2026

A dual-reporter mouse for therapeutic discovery in Angelman syndrome.

Angelman syndrome is a neurodevelopmental disorder caused by loss of the maternal UBE3A allele, the sole source of UBE3A in mature neurons owing to epigenetic silencing of the paternal allele. Although emerging therapies are being developed to restore UBE3A expression by activating the dormant paternal UBE3A allele, existing mouse models for such preclinical studies have limited throughput and utility, creating bottlenecks for both in vitro therapeutic screening and in vivo characterization. To address this, we developed the Ube3a-INSG dual-reporter knockin mouse, in which an IRES-Nanoluciferase-T2A-Sun1-sfGFP (INSG) cassette was inserted downstream of the endogenous Ube3a stop codon. The INSG model preserves UBE3A protein levels and function while enabling 2 complementary allele-specific readouts: Sun1-sfGFP and Nanoluciferase. We show that Sun1-sfGFP, a nuclear envelope-localized reporter, enables single-cell fluorescence analysis, whole-brain light-sheet imaging, and nuclear quantification by flow cytometry. Further, Nanoluciferase supports high-throughput luminescence assays for sensitive pharmacological profiling in cultured neurons and noninvasive in vivo bioluminescence imaging for pharmacodynamic assessment. By combining scalable screening, cellular analysis, and real-time in vivo monitoring in a single model, the Ube3a-INSG dual-reporter mouse provides a powerful platform to accelerate therapeutic development centered on UBE3A.

Animals↗

PubMed2003

Aperture modulated arc therapy.

We show that it is possible to translate an intensity modulated radiation therapy (IMRT) treatment plan and deliver it as a single arc. This technique is referred to in this paper as aperture modulation arc therapy (AMAT). During this arc, the MLC leaves do not conform to the projection of the target PTV and the machine output of the accelerator has a constant value. Dose was calculated using the CORVUS 4.0 IMRT system, which uses a pencil beam dose algorithm, and treatments were delivered using a Varian 2100C/D Clinac. Results are presented for a head and neck and a prostate case, showing the equivalence of the IMRT and the translated AMAT delivery. For a prostate AMAT delivery, coronal plane film dose for the IMRT and AMAT deliveries agreed within 7.19 +/- 6.62%. For a meningioma the coronal plane dose distributions were similar to a value of 4.6 +/- 6.62%. Dose to the isocentre was measured as being within 2% of the planned value in both cases.

Algorithms↗

PubMed2003

Incorporating leaf transmission and head scatter corrections into step-and-shoot leaf sequences for IMRT.

PURPOSE: Leaf transmission and head scatter are two important factors that influence intensity-modulated radiation therapy (IMRT) delivery and should be correctly taken into account when generating multileaf collimator (MLC) sequences. Significant discrepancies between the desired and delivered intensity profiles could otherwise result. The purpose of this article is to propose a reliable algorithm to minimize the dosimetric effects caused by the two factors in step-and-shoot mode. MATERIALS AND METHODS: The goal of the algorithm is to minimize the difference between the desired fluence map and the fluence map actually delivered. For this purpose, an error function, defined as the least-square difference between the desired and the delivered fluence maps, is introduced. The effects of transmission and head scatter are minimized by adjusting the fractional monitor units (MUs) in the initial MLC sequences, created by using the desired fluence map without inclusion of the contributions from the two factors. Computationally, a downhill simplex optimization method is used to minimize the error function with respect to the fractional MUs. A three-source model is used to evaluate the relative head scatter distribution for each segment at the beginning of the calculation. The algorithm has been assessed by comparing the dose distributions delivered by the corrected leaf sequence files and the theoretic predication, calculated by Monte Carlo simulation using the desired fluence maps, for an intuitive test field and several clinical IMRT cases. RESULTS: The deviations between the desired fluence maps and those calculated using the corrected leaf sequence files are <0.3% of the maximum MU for the test field and <1.0% for the clinical IMRT cases. The experimental data show that both absolute and relative dose distributions delivered by the corrected leaf sequences agree with the desired ones within 2.5% of the maximum dose or 2 mm in high-dose gradient regions. Compared with the results obtained by using the leaf sequences in which only the transmission or none of the two effects is corrected, significant improvements in the fluence and dose distributions have been observed. CONCLUSIONS: Transmission and head scatter play important roles in the dosimetric behavior of IMRT delivery. A larger error may result if only one factor is considered because of the opposite effects of the two factors. We noted that the influence of the two effects is more pronounced in absolute dose than in the relative dose. The algorithm proposed in this work accurately corrects for these two effects in step-and-shoot delivery and provides a reliable tool for clinical IMRT application.

Algorithms↗

PubMed2003

Plug pattern optimization for gamma knife radiosurgery treatment planning.

PURPOSE: To develop a novel dose optimization algorithm for improving the sparing of critical structures during gamma knife radiosurgery by shaping the plug pattern of each individual shot. METHOD AND MATERIALS: We first use a geometric information (medial axis) aided guided evolutionary simulated annealing (GESA) optimization algorithm to determine the number of shots and isocenter location, size, and weight of each shot. Then we create a plug quality score system that checks the dose contribution to the volume of interest by each plug in the treatment plan. A positive score implies that the corresponding source could be open to improve tumor coverage, whereas a negative score means the source could be blocked for the purpose of sparing normal and critical structures. The plug pattern is then optimized via the GESA algorithm that is integrated with this score system. Weight and position of each shot are also tuned in this procedure. RESULTS: An acoustic tumor case is used to evaluate our algorithm. Compared to the treatment plan generated without plug patterns, adding an optimized plug pattern into the treatment planning process boosts tumor coverage index from 95.1% to 97.2%, reduces RTOG conformity index from 1.279 to 1.167, lowers Paddick's index from 1.34 to 1.20, and trims the critical structure receiving more than 30% maximum dose from 16 mm(3) to 6 mm(3). CONCLUSIONS: Automated GESA-based plug pattern optimization of gamma knife radiosurgery frees the treatment planning team from the manual forward planning procedure and provides an optimal treatment plan.

Algorithms↗

PubMed2003

Using the volumetric effect of a finite-sized detector for routine quality assurance of multileaf collimator leaf positioning.

Intensity modulated radiation therapy (IMRT) is an advanced form of radiation therapy and promises to improve dose conformation while reducing the irradiation to the sensitive structures. The modality is, however, more complicated than conventional treatment and requires much more stringent quality assurance (QA) to ensure what has been planned can be achieved accurately. One of the main QA tasks is the assurance of positioning accuracy of multileaf collimator (MLC) leaves during IMRT delivery. Currently, the routine quality assurance of MLC in most clinics isbeing done using radiographic films with specially designed MLC leaf sequences. Besides being time consuming, the results of film measurements are difficult to quantify and interpret. In this work, we propose a new and effective technique for routine MLC leaf positioning QA. The technique utilizes the fact that, when a finite-sized detector is placed under a leaf, the relative output of the detector will depend on the relative fractional volume irradiated. A small error in leaf positioning would change the fractional volume irradiated and lead to a deviation of the relative output from the normal reading. For a given MLC and detector system, the relation between the relative output and the leaf displacement can be easily established through experimental measurements and used subsequently as a quantitative means for detecting possible leaf positional errors. The method was tested using a linear accelerator with an 80-leaf MLC. Three different locations, including two locations on central plane (X1 = X2 = 0) and one point on an off-central plane location (X1 = -7.5, X = 7.5), were studied. Our results indicated that the method could accurately detect a leaf positional change of approximately 0.1 mm. The method was also used to monitor the stability of MLC leaf positioning for five consecutive weeks. In this test, we intentionally introduced two positional errors in the testing MLC leaf sequences: -0.2 mm and 1.2 mm. The technique was found to be robust and could detect the positional inaccuracy in each week's test. The influence of other possible error sources, including the ion chamber placement, jaw settings, gantry and collimator angle read-outs, and the positioning errors of the adjacent leaves, on detection accuracy were also investigated. The principle of our method is independent of the types of the MLC and the detector and may have significant practical implications in facilitating routine MLC QA for IMRT delivery.

Calibration↗

PubMed2003

IMRT dose shaping with regionally variable penalty scheme.

A commonly known deficiency of currently available inverse planning systems is the difficulty in fine-tuning the final dose distribution. In practice, it is not uncommon that just a few unsatisfactory regions in the planning target volume or an organ at risk prevent an intensity modulated radiation therapy (IMRT) plan from being clinically acceptable. The purpose of this work is to introduce a mechanism for controlling the regional doses after a conventional IMRT plan is obtained and to demonstrate its clinical utility. Two types of importance factors are introduced in the objective function to model the tradeoffs of different clinical objectives. The first is the conventional structure-dependent importance factor, which quantifies the interstructure tradeoff. The second type is the voxel-dependent importance factor which "modulates" the importance of different voxels within a structure. The planning proceeds in two major steps. First a conventional inverse planning is performed, where the structure-dependent importance factors are determined in a trial-and-error fashion. The next level of planning involves fine-tuning the regional doses to meet specific clinical requirements. To achieve this, the voxels where doses need to be modified are identified either graphically on the isodose layouts, or on the corresponding dose-volume histogram (DVH) curves. The importance value of these voxels is then adjusted to increase/decrease the penalty at the corresponding regions. The technique is applied to two clinical cases. It was found that both tumor hot spots and critical structure maximal doses can be easily controlled by varying the regional penalty. One to three trials were sufficient for the conventionally optimized dose distributions to be adjusted to meet clinical expectation. Thus introducing the voxel-dependent penalty scheme provides an effective means for IMRT dose distributions painting and sculpting.

Algorithms↗

PubMed2003

Therapeutic treatment plan optimization with probability density-based dose prescription.

The dose optimization in inverse planning is realized under the guidance of an objective function. The prescription doses in a conventional approach are usually rigid values, defining in most instances an ill-conditioned optimization problem. In this work, we propose a more general dose optimization scheme based on a statistical formalism [Xing et al., Med. Phys. 21, 2348-2358 (1999)]. Instead of a rigid dose, the prescription to a structure is specified by a preference function, which describes the user's preference over other doses in case the most desired dose is not attainable. The variation range of the prescription dose and the shape of the preference function are predesigned by the user based on prior clinical experience. Consequently, during the iterative optimization process, the prescription dose is allowed to deviate, with a certain preference level, from the most desired dose. By not restricting the prescription dose to a fixed value, the optimization problem becomes less ill-defined. The conventional inverse planning algorithm represents a special case of the new formalism. An iterative dose optimization algorithm is used to optimize the system. The performance of the proposed technique is systematically studied using a hypothetical C-shaped tumor with an abutting circular critical structure and a prostate case. It is shown that the final dose distribution can be manipulated flexibly by tuning the shape of the preference function and that using a preference function can lead to optimized dose distributions in accordance with the planner's specification. The proposed framework offers an effective mechanism to formalize the planner's priorities over different possible clinical scenarios and incorporate them into dose optimization. The enhanced control over the final plan may greatly facilitate the IMRT treatment planning process.

Algorithms↗

PubMed2003

Guidance document on delivery, treatment planning, and clinical implementation of IMRT: report of the IMRT Subcommittee of the AAPM Radiation Therapy Committee.

Intensity-modulated radiation therapy (IMRT) represents one of the most significant technical advances in radiation therapy since the advent of the medical linear accelerator. It allows the clinical implementation of highly conformal nonconvex dose distributions. This complex but promising treatment modality is rapidly proliferating in both academic and community practice settings. However, these advances do not come without a risk. IMRT is not just an add-on to the current radiation therapy process; it represents a new paradigm that requires the knowledge of multimodality imaging, setup uncertainties and internal organ motion, tumor control probabilities, normal tissue complication probabilities, three-dimensional (3-D) dose calculation and optimization, and dynamic beam delivery of nonuniform beam intensities. Therefore, the purpose of this report is to guide and assist the clinical medical physicist in developing and implementing a viable and safe IMRT program. The scope of the IMRT program is quite broad, encompassing multileaf-collimator-based IMRT delivery systems, goal-based inverse treatment planning, and clinical implementation of IMRT with patient-specific quality assurance. This report, while not prescribing specific procedures, provides the framework and guidance to allow clinical radiation oncology physicists to make judicious decisions in implementing a safe and efficient IMRT program in their clinics.

Algorithms↗

PubMed2002

Incorporating prior knowledge into beam orientation optimization in IMRT.

PURPOSE: Selection of beam configuration in currently available intensity-modulated radiotherapy (IMRT) treatment planning systems is still based on trial-and-error search. Computer beam orientation optimization has the potential to improve the situation, but its practical implementation is hindered by the excessive computing time associated with the calculation. The purpose of this work is to provide an effective means to speed up the beam orientation optimization by incorporating a priori geometric and dosimetric knowledge of the system and to demonstrate the utility of the new algorithm for beam placement in IMRT. METHODS AND MATERIALS: Beam orientation optimization was performed in two steps. First, the quality of each possible beam orientation was evaluated using beam's-eye-view dosimetrics (BEVD) developed in our previous study. A simulated annealing algorithm was then employed to search for the optimal set of beam orientations, taking into account the BEVD scores of different incident beam directions. During the calculation, sampling of gantry angles was weighted according to the BEVD score computed before the optimization. A beam direction with a higher BEVD score had a higher probability of being included in the trial configuration, and vice versa. The inclusion of the BEVD weighting in the stochastic beam angle sampling process made it possible to avoid spending valuable computing time unnecessarily at "bad" beam angles. An iterative inverse treatment planning algorithm was used for beam intensity profile optimization during the optimization process. The BEVD-guided beam orientation optimization was applied to an IMRT treatment of paraspinal tumor. The advantage of the new optimization algorithm was demonstrated by comparing the calculation with the conventional scheme without the BEVD weighting in the beam sampling. RESULTS: The BEVD tool provided useful guidance for the selection of the potentially good directions for the beams to incident and was used to guide the search for the optimal beam configuration. The BEVD-guided sampling improved both optimization speed and convergence of the calculation. A comparison of several five-field IMRT treatment plans obtained with and without BEVD guidance indicated that the computational efficiency was increased by a factor of approximately 10. CONCLUSION: Incorporation of BEVD information allows for development of a more robust tool for beam orientation optimization in IMRT planning. It enables us to more effectively use the angular degree of freedom in IMRT without paying the excessive computing overhead and brings us one step closer to the goal of automated selection of beam orientations in a clinical environment.

Algorithms↗

PubMed2002

(-)-Stepholidine promotes proliferation and neuronal differentiation of rat embryonic striatal precursor cells in vitro.

The present study investigated the influence of (-)-stepholidine, an effective dopamine D1 receptor agonist and D2 receptor antagonist, on the development of neural precursor cells. Incubation of striatal neural precursor cells with stepholidine resulted in significant increase in the number of proliferating precursor cell spheres when in the presence of fibroblast growth factor-2. This action can be blocked by application of haloperidol. Treatment with stepholidine also increased the number of microtubule-associated protein-2-immunoreactive cells in the cultures and promoted marked increases in tyrosine hydroxylase expression. These findings suggest that stepholidine is involved in the regulation of proliferation of precursor cells. The effect appears to be mediated by dopamine receptors. Stepholidine also promotes the differentiation of precursor cells, however, this action may be independent of its effect on dopaminergic receptors.

Animals↗

PubMed2002

Inverse planning for functional image-guided intensity-modulated radiation therapy.

Radiation therapy is an image-guided process whose success critically depends on the imaging modality used for treatment planning and the level of integration of the available imaging information. In this work, we establish a dose optimization framework for incorporating metabolic information from functional imaging modalities into the intensity-modulated radiation therapy (IMRT) inverse planning process and to demonstrate the technical feasibility of planning deliberately non-uniform dose distributions in accordance with functional imaging data. For this purpose, a metabolic map from functional images is discretized into a number of abnormality levels (ALs) and then fused with CT images. To escalate dose to the metabolically abnormal regions, we assume, for a given spatial point, a linear relation between the AL and the prescribed dose. But the formalism developed here is independent of the assumption and any other relation between AL and prescription is applicable. For a given AL and prescription relation, it is only necessary to prescribe the dose to the lowest AL in the target and the desired doses to other regions with higher AL values are scaled accordingly. To accomplish differential sparing of a sensitive structure when its functional importance (FI) distribution is known, we individualize the tolerance doses of the voxels within the structure according to their Fl levels. An iterative inverse planning algorithm in voxel domain is used to optimize the system with in homogeneous dose prescription. To model intra-structural trade-off, a mechanism is introduced through the use of voxel-dependent weighting factors, in addition to the conventional structure specific weighting factors which model the inter-structural trade-off. The system is used to plan a phantom case with a few hypothetical functional distributions and a brain tumour treatment with incorporation of magnetic resonance spectroscopic imaging data. The results indicated that it is technically feasible to produce deliberately non-uniform dose distributions according to the functional imaging requirements. Integration of functional imaging information into radiation therapy dose optimization allows for consideration of patient-specific biologic information and provides a significant opportunity to truly individualize radiation treatment. This should enhance our capability to safely and intelligently escalate dose and lays the technical foundation for future clinical studies of the efficacy of functional imaging-guided IMRT.

Algorithms↗

PubMed2002

Examination of the effect of increasing the number of radiation beams on a radiation treatment plan.

Within the confines of least-squares operations, it is possible to quantify the effect of the addition of treatment fields or beamlets to a treatment plan. Using linear algebra and eigenvalue perturbation theory, the effect of the increase in number of treatments is shown to be equivalent to adding a perturbation operator. The effect of adding additional fields will be negligible if the perturbation operator is small. The correspondence of this approach to an earlier work in beam-orientation optimization is also demonstrated. Results are presented for prostate, spinal and head and neck cases, and the connection to beam-orientation optimization is examined.

Dose-Response Relationship, Radiation↗

PubMed2002

Using voxel-dependent importance factors for interactive DVH-based dose optimization.

Intensity modulated radiation therapy (IMRT) inverse planning is usually performed by pre-selecting parameters such as beam modality, beam configuration and importance factors and then optimizing the fluence profiles or beamlet weights. In reality, the IMRT dose optimization problem may be ill-conditioned and there may not be a physical solution to account for the chosen parameters and constraints. Planner intervention is often required to conduct a multiple trial-and-error process where several parameters are sequentially varied until an acceptable compromise is achieved. The resulting solution reflects a balance between the conflicting requirements of the target and the sensitive structures. A major problem of the conventional inverse planning formalism is that there exists no effective mechanism for a planner to fine-tune the dose distribution on a local level or to differentially modify the dose-volume histograms (DVHs) of the involved structures. In this paper we introduce a new inverse planning scheme with voxel-dependent importance factors and demonstrate that it provides us with an effective link between the system parameters and the dosimetric behaviour at a local level. The planning proceeds in two steps. After a conventional trial-and-error inverse planning procedure is completed, we identify the dose interval at which the fractional volume on the DVH curve needs to be changed. The voxels that receive dose in the selected range are then located and their voxel-dependent importance factors are adjusted accordingly. The fine-tuning of the DVHs is iterative in nature and, using widely available computer graphic software tools, the process can be made graphically interactive. The new IMRT planning scheme is applied to two test cases and the results indicate that our control over the differential shapes of the DVHs of the involved structures is,greatly enhanced. Thus the technique may have significant practical implications in facilitating the IMRT treatment planning process.

Algorithms↗

PubMed2002

Independent monitor unit calculation for intensity modulated radiotherapy using the MIMiC multileaf collimator.

A self-consistent monitor unit (MU) and isocenter point-dose calculation method has been developed that provides an independent verification of the MU for intensity modulated radiotherapy (IMRT) using the MIMiC (Nomos Corporation) multileaf collimator. The method takes into account two unique features of IMRT using the MIMiC: namely the gantry-dynamic arc delivery of intensity modulated photon beams and the slice-by-slice dose delivery for large tumor volumes. The method converts the nonuniform beam intensity planned at discrete gantry angles of 5 degrees or 10 degrees into conventional nonmodulated beam intensity apertures of elemental arc segments of 1 degree. This approach more closely simulates the actual gantry-dynamic arc delivery by MIMiC. Because each elemental arc segment is of uniform intensity, the MU calculation for an IMRT arc is made equivalent to a conventional arc with gantry-angle dependent beam apertures. The dose to the isocenter from each 1 degree elemental arc segment is calculated by using the Clarkson scatter summation technique based on measured tissue-maximum-ratio and output factors, independent of the dose calculation model used in the IMRT planning system. For treatments requiring multiple treatment slices, the MU for the arc at each treatment slice takes into account the MU, leakage and scatter doses from other slices. This is achieved by solving a set of coupled linear equations for the MUs of all involved treatment slices. All input dosimetry data for the independent MU/isocenter point-dose calculation are measured directly. Comparison of the MU and isocenter point dose calculated by the independent program to those calculated by the Corvus planning system and to direct measurements has shown good agreement with relative difference less than +/-3%. The program can be used as an independent initial MU verification for IMRT plans using the MIMiC multileaf collimators.

Algorithms↗

PubMed2002

A three-source model for the calculation of head scatter factors.

Accurate determination of the head scatter factor Sc is an important issue, especially for intensity modulated radiation therapy, where the segmented fields are often very irregular and much less than the collimator jaw settings. In this work, we report an Sc calculation algorithm for symmetric, asymmetric, and irregular open fields shaped by the tertiary collimator (a multileaf collimator or blocks) at different source-to-chamber distance. The algorithm was based on a three-source model, in which the photon radiation to the point of calculation was treated as if it originated from three effective sources: one source for the primary photons from the target and two extra-focal photon sources for the scattered photons from the primary collimator and the flattening filter, respectively. The field mapping method proposed by Kim et al. [Phys. Med. Biol. 43, 1593-1604 (1998)] was extended to two extra-focal source planes and the scatter contributions were integrated over the projected areas (determined by the detector's eye view) in the three source planes considering the source intensity distributions. The algorithm was implemented using Microsoft Visual C/C++ in the MS Windows environment. The only input data required were head scatter factors for symmetric square fields, which are normally acquired during machine commissioning. A large number of different fields were used to evaluate the algorithm and the results were compared with measurements. We found that most of the calculated Sc's agreed with the measured values to within 0.4%. The algorithm can also be easily applied to deal with irregular fields shaped by a multileaf collimator that replaces the upper or lower collimator jaws.

Algorithms↗