Browsing by Subject "Organs at Risk"

Now showing 1 - 6 of 6
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    ItemOpen Access
    A Collimator Setting Optimization Algorithm for Dual-Arc Volumetric Modulated Arc Therapy in Pancreas Stereotactic Body Radiation Therapy.
    (Technology in cancer research & treatment, 2019-01) Li, Xinyi; Wu, Jackie; Palta, Manisha; Zhang, You; Sheng, Yang; Zhang, Jiahan; Wang, Chunhao
    PURPOSE:To optimize collimator setting to improve dosimetric quality of pancreas volumetric modulated arc therapy plan for stereotactic body radiation therapy. MATERIALS AND METHODS:Fifty-five volumetric modulated arc therapy cases in stereotactic body radiation therapy of pancreas were retrospectively included in this study with internal review board approval. Different from the routine practice of initializing collimator settings with a template, the proposed algorithm simultaneously optimizes the collimator angles and jaw positions that are customized to the patient geometry. Specifically, this algorithm includes 2 key steps: (1) an iterative optimization algorithm via simulated annealing that generates a set of potential collimator settings from 39 cases with pancreas stereotactic body radiation therapy, and (2) a multi-leaf collimator modulation scoring system that makes the final decision of the optimal collimator settings (collimator angles and jaw positions) based on organs at risk sparing criteria. For validation, the other 16 cases with pancreas stereotactic body radiation therapy were analyzed. Two plans were generated for each validation case, with one plan optimized using the proposed algorithm (Planopt) and the other plan with the template setting (Planconv). Each plan was optimized with 2 full arcs and the same set of constraints for the same case. Dosimetric results were analyzed and compared, including target dose coverage, conformity, organs at risk maximum dose, and modulation complexity score. All results were tested by Wilcoxon signed rank tests, and the statistical significance level was set to .05. RESULTS:Both plan groups had comparable target dose coverage and mean doses of all organs at risk. However, organs at risk (stomach, duodenum, large/small bowel) maximum dose sparing (D0.1 cc and D0.03 cc) was improved in Planopt compared to Planconv. Planopt also showed lower modulation complexity score, which suggests better capability of handling complex shape and sparing organs at risk . CONCLUSIONS:The proposed collimator settings optimization algorithm successfully improved dosimetric performance for dual-arc pancreas volumetric modulated arc therapy plans in stereotactic body radiation therapy of pancreas. This algorithm has the capability of immediate clinical application.
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    Adaptive stereotactic body radiation therapy planning for lung cancer.
    (Int J Radiat Oncol Biol Phys, 2013-09-01) Qin, Y; Zhang, F; Yoo, DS; Kelsey, CR; Yin, FF; Cai, J
    PURPOSE: To investigate the dosimetric effects of adaptive planning on lung stereotactic body radiation therapy (SBRT). METHODS AND MATERIALS: Forty of 66 consecutive lung SBRT patients were selected for a retrospective adaptive planning study. CBCT images acquired at each fraction were used for treatment planning. Adaptive plans were created using the same planning parameters as the original CT-based plan, with the goal to achieve comparable comformality index (CI). For each patient, 2 cumulative plans, nonadaptive plan (PNON) and adaptive plan (PADP), were generated and compared for the following organs-at-risks (OARs): cord, esophagus, chest wall, and the lungs. Dosimetric comparison was performed between PNON and PADP for all 40 patients. Correlations were evaluated between changes in dosimetric metrics induced by adaptive planning and potential impacting factors, including tumor-to-OAR distances (dT-OAR), initial internal target volume (ITV1), ITV change (ΔITV), and effective ITV diameter change (ΔdITV). RESULTS: 34 (85%) patients showed ITV decrease and 6 (15%) patients showed ITV increase throughout the course of lung SBRT. Percentage ITV change ranged from -59.6% to 13.0%, with a mean (±SD) of -21.0% (±21.4%). On average of all patients, PADP resulted in significantly (P=0 to .045) lower values for all dosimetric metrics. ΔdITV/dT-OAR was found to correlate with changes in dose to 5 cc (ΔD5cc) of esophagus (r=0.61) and dose to 30 cc (ΔD30cc) of chest wall (r=0.81). Stronger correlations between ΔdITV/dT-OAR and ΔD30cc of chest wall were discovered for peripheral (r=0.81) and central (r=0.84) tumors, respectively. CONCLUSIONS: Dosimetric effects of adaptive lung SBRT planning depend upon target volume changes and tumor-to-OAR distances. Adaptive lung SBRT can potentially reduce dose to adjacent OARs if patients present large tumor volume shrinkage during the treatment.
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    Dosimetric assessment of rigid setup error by CBCT for HN-IMRT.
    (Journal of applied clinical medical physics, 2010-05-28) Worthy, Danielle; Wu, Qiuwen
    Dose distributions in HN-IMRT are complex and may be sensitive to the treatment uncertainties. The goals of this study were to evaluate: 1) dose differences between plan and actual delivery and implications on margin requirement for HN-IMRT with rigid setup errors; 2) dose distribution complexity on setup error sensitivity; and 3) agreement between average dose and cumulative dose in fractionated radiotherapy. Rigid setup errors for HN-IMRT patients were measured using cone-beam CT (CBCT) for 30 patients and 896 fractions. These were applied to plans for 12HN patients who underwent simultaneous integrated boost (SIB) IMRT treatment. Dose distributions were recalculated at each fraction and summed into cumulative dose. Measured setup errors were scaled by factors of 2-4 to investigate margin adequacy. Two plans, direct machine parameter optimization (DMPO) and fluence only (FO), were available for each patient to represent plans of different complexity. Normalized dosimetric indices, conformity index (CI) and conformation number (CN) were used in the evaluation. It was found that current 5 mm margins are more than adequate to compensate for rigid setup errors, and that standard margin recipes overestimate margins for rigid setup error in SIB HN-IMRT because of differences in acceptance criteria used in margin evaluation. The CTV-to-PTV margins can be effectively reduced to 1.9 mm and 1.5 mm for CTV1 and CTV2. Plans of higher complexity and sharper dose gradients are more sensitive to setup error and require larger margins. The CI and CN are not recommended for cumulative dose evaluation because of inconsistent definition of target volumes used. For fractionated radiotherapy in HN-IMRT, the average fractional dose does not represent the true cumulative dose received by the patient through voxel-by-voxel summation, primarily due to the setup error characteristics, where the random component is larger than systematic and different target regions get underdosed at each fraction.
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    Evaluation of dosimetric uncertainty caused by MR geometric distortion in MRI-based liver SBRT treatment planning.
    (Journal of applied clinical medical physics, 2019-02) Han, Silu; Yin, Fang-Fang; Cai, Jing
    PURPOSE:MRI-based treatment planning is a promising technique for liver stereotactic-body radiation therapy (SBRT) treatment planning to improve target volume delineation and reduce radiation dose to normal tissues. MR geometric distortion, however, is a source of potential error in MRI-based treatment planning. The aim of this study is to investigate dosimetric uncertainties caused by MRI geometric distortion in MRI-based treatment planning for liver SBRT. MATERIALS AND METHODS:The study was conducted using computer simulations. 3D MR geometric distortion was simulated using measured data in the literature. Planning MR images with distortions were generated by integrating the simulated 3D MR geometric distortion onto planning CT images. MRI-based treatment plans were then generated on the planning MR images with two dose calculation methods: (1) using original CT numbers; and (2) using organ-specific assigned CT numbers. Dosimetric uncertainties of various dose-volume-histogram parameters were determined as their differences between the simulated MRI-based plans and the original clinical CT-based plans for five liver SBRT cases. RESULTS:The average simulated distortion for the five liver SBRT cases was 2.77 mm. In the case of using original CT numbers for dose calculation, the average dose uncertainties for target volumes and critical structures were <0.5 Gy, and the average target volume percentage at prescription dose uncertainties was 0.97%. In the case of using assigned CT numbers, the average dose uncertainties for target volumes and critical structures were <1.0 Gy, and the average target volume percentage at prescription dose uncertainties was 2.02%. CONCLUSIONS:Dosimetric uncertainties caused by MR geometric distortion in MRI-based liver SBRT treatment planning was generally small (<1 Gy) when the distortion is 3 mm.
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    Novel Manganese-Porphyrin Superoxide Dismutase-Mimetic Widens the Therapeutic Margin in a Preclinical Head and Neck Cancer Model.
    (International journal of radiation oncology, biology, physics, 2015-11) Ashcraft, Kathleen A; Boss, Mary-Keara; Tovmasyan, Artak; Roy Choudhury, Kingshuk; Fontanella, Andrew N; Young, Kenneth H; Palmer, Gregory M; Birer, Samuel R; Landon, Chelsea D; Park, Won; Das, Shiva K; Weitner, Tin; Sheng, Huaxin; Warner, David S; Brizel, David M; Spasojevic, Ivan; Batinic-Haberle, Ines; Dewhirst, Mark W

    Purpose

    To test the effects of a novel Mn porphyrin oxidative stress modifier, Mn(III) meso-tetrakis(N-n-butoxyethylpyridinium-2-yl)porphyrin (MnBuOE), for its radioprotective and radiosensitizing properties in normal tissue versus tumor, respectively.

    Methods and materials

    Murine oral mucosa and salivary glands were treated with a range of radiation doses with or without MnBuOE to establish the dose-effect curves for mucositis and xerostomia. Radiation injury was quantified by intravital near-infrared imaging of cathepsin activity, assessment of salivation, and histologic analysis. To evaluate effects of MnBuOE on the tumor radiation response, we administered the drug as an adjuvant to fractionated radiation of FaDu xenografts. Again, a range of radiation therapy (RT) doses was administered to establish the radiation dose-effect curve. The 50% tumor control dose values with or without MnBuOE and dose-modifying factor were determined.

    Results

    MnBuOE protected normal tissue by reducing RT-mediated mucositis, xerostomia, and fibrosis. The dose-modifying factor for protection against xerostomia was 0.77. In contrast, MnBuOE increased tumor local control rates compared with controls. The dose-modifying factor, based on the ratio of 50% tumor control dose values, was 1.3. Immunohistochemistry showed that MnBuOE-treated tumors exhibited a significant influx of M1 tumor-associated macrophages, which provides mechanistic insight into its radiosensitizing effects in tumors.

    Conclusions

    MnBuOE widens the therapeutic margin by decreasing the dose of radiation required to control tumor, while increasing normal tissue resistance to RT-mediated injury. This is the first study to quantitatively demonstrate the magnitude of a single drug's ability to radioprotect normal tissue while radiosensitizing tumor.
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    Quantitative comparison of automatic and manual IMRT optimization for prostate cancer: the benefits of DVH prediction.
    (Journal of applied clinical medical physics, 2015-03-08) Yang, Yun; Li, Taoran; Yuan, Lunlin; Ge, Yaorong; Yin, Fang-Fang; Lee, W Robert; Wu, Q Jackie
    A recent publication indicated that the patient anatomical feature (PAF) model was capable of predicting optimal objectives based on past experience. In this study, the benefits of IMRT optimization using PAF-predicted objectives as guidance for prostate were evaluated. Three different optimization methods were compared.1) Expert Plan: Ten prostate cases (16 plans) were planned by an expert planner using conventional trial-and-error approach started with institutional modified OAR and PTV constraints. Optimization was stopped at 150 iterations and that plan was saved as Expert Plan. 2) Clinical Plan: The planner would keep working on the Expert Plan till he was satisfied with the dosimetric quality and the final plan was referred to as Clinical Plan. 3) PAF Plan: A third sets of plans for the same ten patients were generated fully automatically using predicted DVHs as guidance. The optimization was based on PAF-based predicted objectives, and was continued to 150 iterations without human interaction. DMAX and D98% for PTV, DMAX for femoral heads, DMAX, D10cc, D25%/D17%, and D40% for bladder/rectum were compared. Clinical Plans are further optimized with more iterations and adjustments, but in general provided limited dosimetric benefits over Expert Plans. PTV D98% agreed within 2.31% among Expert, Clinical, and PAF plans. Between Clinical and PAF Plans, differences for DMAX of PTV, bladder, and rectum were within 2.65%, 2.46%, and 2.20%, respectively. Bladder D10cc was higher for PAF but < 1.54% in general. Bladder D25% and D40% were lower for PAF, by up to 7.71% and 6.81%, respectively. Rectum D10cc, D17%, and D40% were 2.11%, 2.72%, and 0.27% lower for PAF, respectively. DMAX for femoral heads were comparable (< 35 Gy on average). Compared to Clinical Plan (Primary + Boost), the average optimization time for PAF plan was reduced by 5.2 min on average, with a maximum reduction of 7.1min. Total numbers of MUs per plan for PAF Plans were lower than Clinical Plans, indicating better delivery efficiency. The PAF-guided planning process is capable of generating clinical-quality prostate IMRT plans with no human intervention. Compared to manual optimization, this automatic optimization increases planning and delivery efficiency, while maintainingplan quality.