Dosimetric comparison of ZAP-X, Gamma Knife, and CyberKnife stereotactic radiosurgery for single brain metastasis.

PURPOSE: To evaluate the dosimetric characteristics of ZAP-X stereotactic radiosurgery (SRS) for single brain metastasis by comparing with two mature SRS platforms. METHODS: Thirteen patients with single brain metastasis treated with CyberKnife (CK) G4 were selected retrospectively. The prescription dose for the planning target volume (PTV) was 18-24 Gy for 1-3 fractions. The PTV volume ranged from 0.44 to 11.52 cc.Treatment plans of thirteen patients were replanned using the ZAP-X plan system and the Gamma Knife (GK) ICON plan system with the same prescription dose and organs at risk (OARs) constraints. The prescription dose of PTV was normalized to 70% for both ZAP-X and CK, while it was 50% for GK. The dosimetric parameters of three groups included the plan characteristics (CI, GI, GSI, beams, MUs, treatment time), PTV (D2, D95, D98, Dmin, Dmean, Coverage), brain tissue (volume of 100%-10% prescription dose irradiation V100%-V10%, Dmean) and other OARs (Dmax, Dmean),all of these were compared and evaluated. All data were read and analyzed with MIM Maestro. One-way ANOVA or a multisample Friedman rank sum test was performed, where p < 0.05 indicated significant differences. RESULTS: The CI of GK was significantly lower than that of ZAP-X and CK. Regarding the mean value, ZAP-X had a lower GI and higher GSI, but there was no significant difference among the three groups. The MUs of ZAP-X were significantly lower than those of CK, and the mean value of the treatment time of ZAP-X was significantly shorter than that of CK. For PTV, the D95, D98, and target coverage of CK were higher, while the mean of Dmin of GK was significantly lower than that of CK and ZAP-X. For brain tissue, ZAP-X showed a smaller volume from V100% to V20%; the statistical results of V60% and V50% showed a difference between ZAP-X and GK, while the V40% and V30% showed a significant difference between ZAP-X and the other two groups; V10% and Dmean indicated that GK was better. Excluding the Dmax of the brainstem, right optic nerve and optic chiasm, the mean value of all other OARs was less than 1 Gy. For the brainstem, GK and ZAP-X had better protection, especially at the maximum dose. CONCLUSION: For the SRS treating single brain metastasis, all three treatment devices, ZAP-X system, CyberKnife G4 system, and GammaKnife system, could meet clinical treatment requirements. The newly platform ZAP-X could provide a high-quality plan equivalent to or even better than CyberKnife and Gamma Knife, with ZAP-X presenting a certain dose advantage, especially with a more conformal dose distribution and better protection for brain tissue. As the ZAP-X systems get continuous improvements and upgrades, they may become a new SRS platform for the treatment of brain metastasis.

Spatial proteomic profiling elucidates immune determinants of neoadjuvant chemo-immunotherapy in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) presents significant clinical and therapeutic challenges due to its aggressive nature and generally poor prognosis. We initiated a Phase II clinical trial (ChiCTR1900027160) to assess the efficacy of a pioneering neoadjuvant chemo-immunotherapy regimen comprising programmed death-1 (PD-1) blockade (Toripalimab), nanoparticle albumin-bound paclitaxel (nab-paclitaxel), and the oral fluoropyrimidine derivative S-1, in patients with locally advanced ESCC. This study uniquely integrates clinical outcomes with advanced spatial proteomic profiling using Imaging Mass Cytometry (IMC) to elucidate the dynamics within the tumor microenvironment (TME), focusing on the mechanistic interplay of resistance and response. Sixty patients participated, receiving the combination therapy prior to surgical resection. Our findings demonstrated a major pathological response (MPR) in 62% of patients and a pathological complete response (pCR) in 29%. The IMC analysis provided a detailed regional assessment, revealing that the spatial arrangement of immune cells, particularly CD8+ T cells and B cells within tertiary lymphoid structures (TLS), and S100A9+ inflammatory macrophages in fibrotic regions are predictive of therapeutic outcomes. Employing machine learning approaches, such as support vector machine (SVM) and random forest (RF) analysis, we identified critical spatial features linked to drug resistance and developed predictive models for drug response, achieving an area under the curve (AUC) of 97%. These insights underscore the vital role of integrating spatial proteomics into clinical trials to dissect TME dynamics thoroughly, paving the way for personalized and precise cancer treatment strategies in ESCC. This holistic approach not only enhances our understanding of the mechanistic basis behind drug resistance but also sets a robust foundation for optimizing therapeutic interventions in ESCC.

Application of MR images in radiotherapy planning for brain tumor based on deep learning.

PURPOSE: Explore the function and dose calculation accuracy of MRI images in radiotherapy planning through deep learning methods. METHODS: 131 brain tumor patients undergoing radiotherapy with previous MR and CT images were recruited for this study. A new series of MRI from the aligned MR was firstly registered to CT images strictly using MIM software and then resampled. A deep learning method (U-NET) was used to establish a MRI-to-CT conversion model, for which 105 patient images were used as the training set and 26 patient images were used as the tuning set. Data from additional 8 patients were collected as the test set, and the accuracy of the model was evaluated from a dosimetric standpoint. RESULTS: Comparing the synthetic CT images with the original CT images, the difference in dosimetric parameters D98, D95, D2 and Dmean of PTV in 8 patients was less than 0.5%. The gamma passed rates of PTV and whole body volume were: 1%/1 mm: 93.96%±6.75%, 2%/2 mm: 99.87%±0.30%, 3%/3 mm: 100.00%±0.00%; and 1%/1 mm: 99.14%±0.80%, 2%/2 mm: 99.92%±0.08%, 3%/3 mm: 99.99%±0.01%. CONCLUSION: MR images can be used both in delineation and treatment efficacy evaluation and in dose calculation. Using the deep learning way to convert MR image to CT image is a viable method and can be further used in dose calculation.

Capillarity Enabled Large-Array Liquid Metal Electrodes for Compact and High-Throughput Dielectrophoretic Microfluidics.

Dielectrophoresis (DEP) particle separation has label-free, well-controllable, and low-damage merits. Sidewall microelectrodes made of liquid metal alloy (LMA) inherits the additional advantage of thick electrodes to generate impactful DEP force. However, existing LMA electrode-based devices lack the ability to integrate large-array electrodes in a compact footprint, severely limiting flow rate and thus throughput. Herein, a facile and versatile method is proposed to integrate high-density thick LMA electrodes in microfluidic devices, taking advantage of the passive control ability of capillary burst valves (CBVs). CBVs with carefully designed burst pressures are co-designed in microfluidic channels, allowing self-assembly of LMA electrode array through simple hand-push injection. The arrayed electrode configuration brings the accumulative DEP deflection effect. Specifically, The fabricated 5000 pairs of sidewall electrodes in a compact chip are demonstrted to achieve ten times higher throughput in DEP deflection. The 5000-electrode-pair device is applied to successfully separate four mixed samples, including human peripheral blood mononuclear cells and A549 cells with the flow rate of 70 µL min-1. It is envisioned that this work can greatly facilitate LMA electrode array fabrication and offer a robust and versatile platform for DEP separation applications.

[Automatic Post-operative Cervical Cancer Target Area and Organ at Risk Outlining Based on Fusion Convolutional Neural Network].

CT image based organ segmentation is essential for radiotherapy treatment planning, and it is laborious and time consuming to outline the endangered organs and target areas before making radiation treatment plans. This study proposes a fully automated segmentation method based on fusion convolutional neural network to improve the efficiency of physicians in outlining the endangered organs and target areas. The CT images of 170 postoperative cervical cancer stage IB and IIA patients were selected for network training and automatic outlining of bladder, rectum, femoral head and CTV, and the neural network was used to localize easily distinguishable vessels around the target area to achieve more accurate outlining of CTV.

Hypofractionated radiotherapy in ten fractions for postmastectomy patients: a phase II study compared with another hypofractionation schedule with sixteen fractions.

BACKGROUND: The purpose of this phase II study was to evaluate the feasibility of hypofractionated radiotherapy (HFRT) with a dose of 36.5 Gy in 10 fractions in postmastectomy patients. METHODS: From March 2014 to December 2015, 85 patients with locally advanced breast cancer were eligible to participate in this study with a schedule of 36.5 Gy in 10 fractions. Intensity-modulated radiation therapy (IMRT) was delivered to the chest wall with or without the supraclavicular region. The primary endpoint was radiation-related toxicities. The secondary endpoints were locoregional failure-free survival (LRFFS), disease-free survival (DFS) and overall survival (OS). And the outcomes were compared with our retrospective study of 72 patients with 42.5 Gy in 16 fractions. RESULTS: The median follow-up was 69.0 (range 66.5-71.5) months in the 36.5 Gy group and 93.0 (range 91.9-94.1) months in the 42.5 Gy group, respectively. Radiation-related toxicities were mainly grade 1, although a few patients had grade 2 plexopathy (1.2%) and acute skin toxicity (1.2%) in the 36.5 Gy group, and grade 2 acute skin toxicity (5.6%) and lymphedema (4.2%) in the 42.5 Gy group. There were no significant differences between the groups in acute and late toxicities. For all the patients, the 5-year LRFFS, DFS and OS were 97.7 and 100.0%, 93.1 and 90.3%, 98.8 and 97.2%, respectively, without significant differences between the groups. CONCLUSION: Postmastectomy HFRT with a schedule of 36.5 Gy in 10 fractions was feasible, with mild toxicities and excellent 5-year clinical outcome. TRIAL REGISTRATION: Trial registration number: ChiCTR-ONRC-14004391 . Date of registration: 9/3/2014.

Intraoperative radiotherapy vs concurrent chemoradiotherapy in the treatment of patients with locally advanced pancreatic cancer.

PURPOSE: The purpose of the multi-institutional retrospective study was to evaluate whether intraoperative radiotherapy (IORT) has advantages in the treatment of patients with locally advanced pancreatic cancer (LAPC) compared with concurrent chemoradiotherapy (CCRT). PATIENTS AND METHODS: A total of 103 patients with LAPC whom was treated with IORT (Arm A; n = 50) or CCRT (Arm B; n = 53) from 2015.6 to 2016.7 were retrospectively identified. Data on feasibility, toxicity, and overall survival (OS) were evaluated. RESULTS: Most factors of the two cohorts were similar. The severe adverse events (grade 3 and 4) patients in Arm B were higher than patients in Arm A (34% vs 0%). Disease progression was noted in 38 patients (76%) in Arm A and 37 patients (69.8%) in Arm B. The median survival of patients in Arm A and B were 15.3 months (95% CI, 13.0-17.6 months) and 13.8 months (95% CI, 11.0-16.6 months), respectively. The 1-year survival rate were 66.3% in Arm A (95% CI, 52.3%-80.2%) and 60.9% in Arm B (95% CI, 46.4%-75.4%). There was no significant difference in OS between patients treated with IORT and with CCRT (p = 0.458). CONCLUSION: Our results demonstrated that patients with LAPC treated with IORT showed fewer adverse events, less treatment time, and high feasibility compared to CCRT. Although, IORT has no advantages in survival and tumor control compared with CCRT.

CT based automatic clinical target volume delineation using a dense-fully connected convolution network for cervical Cancer radiation therapy.

BACKGROUND: It is very important to accurately delineate the CTV on the patient's three-dimensional CT image in the radiotherapy process. Limited to the scarcity of clinical samples and the difficulty of automatic delineation, the research of automatic delineation of cervical cancer CTV based on CT images for new patients is slow. This study aimed to assess the value of Dense-Fully Connected Convolution Network (Dense V-Net) in predicting Clinical Target Volume (CTV) pre-delineation in cervical cancer patients for radiotherapy. METHODS: In this study, we used Dense V-Net, a dense and fully connected convolutional network with suitable feature learning in small samples to automatically pre-delineate the CTV of cervical cancer patients based on computed tomography (CT) images and then we assessed the outcome. The CT data of 133 patients with stage IB and IIA postoperative cervical cancer with a comparable delineation scope was enrolled in this study. One hundred and thirteen patients were randomly designated as the training set to adjust the model parameters. Twenty cases were used as the test set to assess the network performance. The 8 most representative parameters were also used to assess the pre-sketching accuracy from 3 aspects: sketching similarity, sketching offset, and sketching volume difference. RESULTS: The results presented that the DSC, DC/mm, HD/cm, MAD/mm, ∆V, SI, IncI and JD of CTV were 0.82 ± 0.03, 4.28 ± 2.35, 1.86 ± 0.48, 2.52 ± 0.40, 0.09 ± 0.05, 0.84 ± 0.04, 0.80 ± 0.05, and 0.30 ± 0.04, respectively, and the results were greater than those with a single network. CONCLUSIONS: Dense V-Net can correctly predict CTV pre-delineation of cervical cancer patients and can be applied in clinical practice after completing simple modifications.

[Automated Pre-delineation of CTV in Patients with Cervical Cancer Using Dense V-Net].

We use a dense and fully connected convolutional network with good feature learning in small samples, to automatically pre-deline CTV of cervical cancer patients based on CT images and evaluate the effect. The CT data of stage IB and IIA postoperative cervical cancer with similar delineation scope were selected to be used to evaluate the pre-sketching accuracy from three aspects:sketching similarity, sketching offset and sketching volume difference. It has been proved that the 8 most representative parameters are superior to those with single network and reported internationally before. Dense V-Net can accurately predict CTV pre-delineation of cervical cancer patients, which can be used clinically after simple modification by doctors.

Automatic segmentation of pelvic organs-at-risk using a fusion network model based on limited training samples.

Background: Efficient and accurate methods are needed to automatically segmenting organs-at-risk (OAR) to accelerate the radiotherapy workflow and decrease the treatment wait time. We developed and evaluated the use of a fused model Dense V-Network for its ability to accurately segment pelvic OAR.Material and methods: We combined two network models, Dense Net and V-Net, to establish the Dense V-Network algorithm. For the training model, we adopted 100 kV computed tomography (CT) images of patients with cervical cancer, including 80 randomly selected as training sets, by which to adjust parameters of the automatic segmentation model, and the remaining 20 as test sets to evaluate the performance of the convolutional neural network model. Three representative parameters were used to evaluate the segmentation results quantitatively.Results: Clinical results revealed that Dice similarity coefficient values of the bladder, small intestine, rectum, femoral head and spinal cord were all above 0.87 mm; and Jaccard distance was within 2.3 mm. Except for the small intestine, the Hausdorff distance of other organs was less than 9.0 mm. Comparison of our approaches with those of the Atlas and other studies demonstrated that the Dense V-Network had more accurate and efficient performance and faster speed.Conclusions: The Dense V-Network algorithm can be used to automatically segment pelvic OARs accurately and efficiently, while shortening patients' waiting time and accelerating radiotherapy workflow.

[A fusion network model based on limited training samples for the automatic segmentation of pelvic endangered organs].

When applying deep learning to the automatic segmentation of organs at risk in medical images, we combine two network models of Dense Net and V-Net to develop a Dense V-network for automatic segmentation of three-dimensional computed tomography (CT) images, in order to solve the problems of degradation and gradient disappearance of three-dimensional convolutional neural networks optimization as training samples are insufficient. This algorithm is applied to the delineation of pelvic endangered organs and we take three representative evaluation parameters to quantitatively evaluate the segmentation effect. The clinical result showed that the Dice similarity coefficient values of the bladder, small intestine, rectum, femoral head and spinal cord were all above 0.87 (average was 0.9); Jaccard distance of these were within 2.3 (average was 0.18). Except for the small intestine, the Hausdorff distance of other organs were less than 0.9 cm (average was 0.62 cm). The Dense V-Network has been proven to achieve the accurate segmentation of pelvic endangered organs.

Dose fall-off during the treatment of thoracic spine metastasis with CyberKnife stereotactic body radiation therapy (SBRT).

CyberKnife stereotactic body radiation therapy (SBRT) is becoming increasingly used for cancer treatment and, to maximize its clinical application, it is important to define the dosimetric characteristics, optimal dose, and fractionation regimens. The aim of this study was to evaluate the dose fall-off in two fractionated regimens of CyberKnife SBRT during the treatment of thoracic spinal metastasis. Patients with spinal metastasis involving a vertebra and pedicle were treated with 40 Gy in 5 fractions (n = 4), and patients with spinal metastasis involving only a vertebra received 33 Gy in 3 fractions (n = 4). A new approach was used to measure absolute dose fall-off distance, relative dose fall-off distance, and the dose fall-off per unit distance along four reference directions in the axial plane. Patients treated with 33 Gy/3 fractions had a greater absolute dose fall-off distance in direction 1 (from the point with maximum dose [Dmax] towards the spinal cord) and direction 3 (the opposite of direction 1), a greater relative dose fall-off distance in direction 3, and a lower dose fall-off per unit distance in direction 1 and 3 compared to patients treated with 40 Gy/5 fractions (all p < 0.05). Overall, the dose fall-off towards the spinal cord is rapid during the treatment of thoracic spinal metastasis with CyberKnife SBRT, which allows a higher dose of radiation to be delivered to the tumor and, at the same time, better protection of the spinal cord.

Reducing Xerostomia by Comprehensive Protection of Salivary Glands in Intensity-Modulated Radiation Therapy with Helical Tomotherapy Technique for Head-and-Neck Cancer Patients: A Prospective Observational Study.

OBJECTIVE: This study aimed to analyze the effects of comprehensive protection of bilateral parotid glands (PG-T), contralateral submandibular gland (cSMG), and accessory salivary glands in the oral cavity (OC) by helical tomotherapy for head-and-neck cancer patients. METHODS: Totally 175 patients with histologically confirmed head-and-neck cancer treated with helical tomotherapy were recruited. The doses delivered to PG-T, cSMG, and OC were constrained to be as low as possible in treatment planning. The saliva flow rates and xerostomia questionnaire were evaluated. Correlation between xerostomia and other clinical factors were assessed using univariate and multivariate models. The impact of salivary gland dose on locoregional (LR) recurrence was assessed by Cox analysis. ROC curve was used to determine the threshold of mean dose for each gland. RESULTS: The median follow-up was 25 (19-36) months. The OC mean dose, PG-T mean dose, cSMG mean dose, age, clinical stage (II and III versus IV), and both unstimulated and stimulated saliva flow rates were significantly correlated with xerostomia. The OC mean dose, cSMG mean dose, age, and clinical stage were predictors of xerostomia after adjusting PG-T mean dose, and unstimulated and stimulated saliva flow rates. Xerostomia was significantly decreased when the mean doses of PG-T, cSMG, and OC were kept below 29.12Gy, 29.29Gy, and 31.44Gy, respectively. At 18 months after radiation therapy, early LR recurrence rate was only 4%. CONCLUSION: Comprehensive protection of salivary glands minimized xerostomia in head-and-neck cancer patients treated by helical tomotherapy, without increasing early LR recurrence risk.

Erratum to "[18F]ML-10 Imaging for Assessment of Apoptosis Response of Intracranial Tumor Early after Radiosurgery by PET/CT".

[This corrects the article DOI: 10.1155/2018/9365174.].

[18F]ML-10 Imaging for Assessment of Apoptosis Response of Intracranial Tumor Early after Radiosurgery by PET/CT.

[18F]ML-10 is a novel apoptosis radiotracer for positron emission tomography (PET). We assess the apoptosis response of intracranial tumor early after CyberKnife (CK) treatment by [18F]ML-10 PET imaging. 29 human subjects (30 lesions), diagnosed with intracranial tumors, underwent CK treatment at 14-24 Gy in 1-3 fractions, had [18F]ML-10 positron emission tomography/computed tomography (PET/CT) before (pre-CK) and 48 hours after (post-CK) CK treatment. Magnetic resonance imaging (MRI) scans were taken before and 8 weeks after CK treatment. Voxel-based analysis was used for the imaging analysis. Heterogeneous changes of apoptosis in tumors before and after treatment were observed on voxel-based analysis of PET images. A positive correlation was observed between the change in radioactivity (X) and subsequent tumor volume (Y) (r=0.862, p < 0.05), with a regression equation of Y=1.018∗X - 0.016. Malignant tumors tend to be more sensitive to CK treatment, but the treatment outcome is not affected by pre-CK apoptotic status of tumor cells; [18F]ML-10 PET imaging could be taken as an assessment 48 h after CK treatment.

Association of DNA repair gene polymorphisms with the risk of radiation pneumonitis in lung cancer patients.

A total of 149 lung cancer patients were recruited to receive intensity modulated radiation therapy (IMRT). The association of developing radiation pneumonitis (RP) with genetic polymorphism was evaluated. The risks of four polymorphic sites in three DNA repair related genes (ERCC1, rs116615:T354C and rs3212986:C1516A; ERCC2, rs13181:A2251C; XRCC1, rs25487:A1196G) for developing grade ≥ 2 RP were assessed respectively. It was observed that ERCC1 T354C SNP had a significant effect on the development of grade ≥ 2 RP (CT/TT vs. CC, adjusted HR = 0.517, 95% CI, 0.285-0.939; adjusted P = 0.030). It is the first time demonstrating that CT/TT genotype of ERCC1 354 was significantly associated with lower RP risk after radio therapy.

Integration of Functional MRI and White Matter Tractography in CyberKnife Radiosurgery.

PURPOSE: To investigate the efficacy of the integration of functional magnetic resonance imaging and diffusion-tensor imaging tractography data into CyberKnife radiosurgery for intracranial tumor management. MATERIALS AND METHODS: Functional neuroimaging, anatomical magnetic resonance imaging, and computed tomography images of patients with brain lesions in critical areas were acquired before radiosurgery. The acquired data sets were coregistered using the MIM image fusion software module and then were imported into the CyberKnife Robotic Radiosurgery System (Multiplan 4.0.2) for delineating the target, organs at risk, and possible nearby functionally relevant cortical and subcortical areas. Radiation dose distributions with and without the functionally relevant cortical and subcortical areas into the optimization process were developed and compared. RESULTS: There were significant differences between the treatment plans with and without the functionally relevant cortical and subcortical areas into the optimization process. An average 22.71% reduction in the maximum dose to functional areas was observed. No neurological complication due to radiation damage was observed in the follow-up period. CONCLUSION: The functional neuroimaging could be easily and reliably integrated into the CyberKnife treatment planning. Consideration of functional structures and fiber tracts during treatment planning could clinically reduce the radiation doses to these critical structures, thereby preserving its unique function of brain.

Dosimetric evaluation of 4 different treatment modalities for curative-intent stereotactic body radiation therapy for isolated thoracic spinal metastases.

To investigate the dosimetric characteristics of 4 SBRT-capable dose delivery systems, CyberKnife (CK), Helical TomoTherapy (HT), Volumetric Modulated Arc Therapy (VMAT) by Varian RapidArc (RA), and segmental step-and-shoot intensity-modulated radiation therapy (IMRT) by Elekta, on isolated thoracic spinal lesions. CK, HT, RA, and IMRT planning were performed simultaneously for 10 randomly selected patients with 6 body types and 6 body + pedicle types with isolated thoracic lesions. The prescription was set with curative intent and dose of either 33Gy in 3 fractions (3F) or 40Gy in 5F to cover at least 90% of the planning target volume (PTV), correspondingly. Different dosimetric indices, beam-on time, and monitor units (MUs) were evaluated to compare the advantages/disadvantages of each delivery modality. In ensuring the dose-volume constraints for cord and esophagus of the premise, CK, HT, and RA all achieved a sharp conformity index (CI) and a small penumbra volume compared to IMRT. RA achieved a CI comparable to those from CK, HT, and IMRT. CK had a heterogeneous dose distribution in the target as its radiosurgical nature with less dose uniformity inside the target. CK had the longest beam-on time and the largest MUs, followed by HT and RA. IMRT presented the shortest beam-on time and the least MUs delivery. For the body-type lesions, CK, HT, and RA satisfied the target coverage criterion in 6 cases, but the criterion was satisfied in only 3 (50%) cases with the IMRT technique. For the body + pedicle-type lesions, HT satisfied the criterion of the target coverage of ≥90% in 4 of the 6 cases, and reached a target coverage of 89.0% in another case. However, the criterion of the target coverage of ≥90% was reached in 2 cases by CK and RA, and only in 1 case by IMRT. For curative-intent SBRT of isolated thoracic spinal lesions, RA is the first choice for the body-type lesions owing to its delivery efficiency (time); the second choice is CK or HT; HT is the preferential choice for the body + pedicle-type lesions. This study suggests further clinical investigations with longer follow-up for these studied cases.

Dose Evaluation of Fractionated Schema and Distance From Tumor to Spinal Cord for Spinal SBRT with Simultaneous Integrated Boost: A Preliminary Study.

BACKGROUND This study investigated and quantified the dosimetric impact of the distance from the tumor to the spinal cord and fractionation schemes for patients who received stereotactic body radiation therapy (SBRT) and hypofractionated simultaneous integrated boost (HF-SIB). MATERIAL AND METHODS Six modified planning target volumes (PTVs) for 5 patients with spinal metastases were created by artificial uniform extension in the region of PTV adjacent spinal cord with a specified minimum tumor to cord distance (0-5 mm). The prescription dose (biologic equivalent dose, BED) was 70 Gy in different fractionation schemes (1, 3, 5, and 10 fractions). For PTV V100, Dmin, D98, D95, and D1, spinal cord dose, conformity index (CI), V30 were measured and compared. RESULTS PTV-to-cord distance influenced PTV V100, Dmin, D98, and D95, and fractionation schemes influenced Dmin and D98, with a significant difference. Distances of ≥2 mm, ≥1 mm, ≥1 mm, and ≥0 mm from PTV to spinal cord meet dose requirements in 1, 3, 5, and 10 fractionations, respectively. Spinal cord dose, CI, and V30 were not impacted by PTV-to-cord distance and fractionation schemes. CONCLUSIONS Target volume coverage, Dmin, D98, and D95 were directly correlated with distance from the spinal cord for spine SBRT and HF-SIB. Based on our study, ≥2 mm, ≥1 mm, ≥1 mm, and ≥0 mm distance from PTV to spinal cord meets dose requirements in 1, 3, 5 and 10 fractionations, respectively.

[Evaluation of the EDOSE for IMRT Delivery Quality Assurance].

Objective: Evaluation of intensity-modulated radiation therapy(IMRT) delivery quality assurance(DQA) using EDOSE software based on accelerator electronic portal imaging device (EPID). Methods: Analysed the dose response uniformity correction of EPID imaging plate in different fields and the gamma pass rates about the fields; And compared the calculated parameters of the EDOSE and the Pinnacle planning station. Results: The uniformities on the homogeneous region of thefi elds are good after who corrected by EDOSE. The gamma(γ, 3mm/3%) pass rates are in the ideal range. The volume of the organs at risk(OAR) have no statistical signifi cance except the right lung; A part of the parameters have statistical signifi cance. Conclusions: The results of the calculation and analysis of EDOSE has a high agreement with the planning system.