Literature DB >> 29131812

An improved distance-to-dose correlation for predicting bladder and rectum dose-volumes in knowledge-based VMAT planning for prostate cancer.

Phillip D H Wall1, Robert L Carver, Jonas D Fontenot.   

Abstract

The overlap volume histogram (OVH) is an anatomical metric commonly used to quantify the geometric relationship between an organ at risk (OAR) and target volume when predicting expected dose-volumes in knowledge-based planning (KBP). This work investigated the influence of additional variables contributing to variations in the assumed linear DVH-OVH correlation for the bladder and rectum in VMAT plans of prostate patients, with the goal of increasing prediction accuracy and achievability of knowledge-based planning methods. VMAT plans were retrospectively generated for 124 prostate patients using multi-criteria optimization. DVHs quantified patient dosimetric data while OVHs quantified patient anatomical information. The DVH-OVH correlations were calculated for fractional bladder and rectum volumes of 30, 50, 65, and 80%. Correlations between potential influencing factors and dose were quantified using the Pearson product-moment correlation coefficient (R). Factors analyzed included the derivative of the OVH, prescribed dose, PTV volume, bladder volume, rectum volume, and in-field OAR volume. Out of the selected factors, only the in-field bladder volume (mean R  =  0.86) showed a strong correlation with bladder doses. Similarly, only the in-field rectal volume (mean R  =  0.76) showed a strong correlation with rectal doses. Therefore, an OVH formalism accounting for in-field OAR volumes was developed to determine the extent to which it improved the DVH-OVH correlation. Including the in-field factor improved the DVH-OVH correlation, with the mean R values over the fractional volumes studied improving from  -0.79 to  -0.85 and  -0.82 to  -0.86 for the bladder and rectum, respectively. A re-planning study was performed on 31 randomly selected database patients to verify the increased accuracy of KBP dose predictions by accounting for bladder and rectum volume within treatment fields. The in-field OVH led to significantly more precise and fewer unachievable KBP predictions, especially for lower bladder and rectum dose-volumes.

Entities:  

Mesh:

Year:  2018        PMID: 29131812     DOI: 10.1088/1361-6560/aa9a30

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  7 in total

Review 1.  Automation in intensity modulated radiotherapy treatment planning-a review of recent innovations.

Authors:  Mohammad Hussein; Ben J M Heijmen; Dirk Verellen; Andrew Nisbet
Journal:  Br J Radiol       Date:  2018-09-04       Impact factor: 3.039

2.  Dose Prediction Models Based on Geometric and Plan Optimization Parameter for Adjuvant Radiotherapy Planning Design in Cervical Cancer Radiotherapy.

Authors:  Hui Tang; Yazheng Chen; Jialiang Jiang; Kemin Li; Jing Zeng; Zhenyao Hu; Rutie Yin
Journal:  J Healthc Eng       Date:  2021-11-12       Impact factor: 2.682

3.  Finite Element-Based Personalized Simulation of Duodenal Hydrogel Spacer: Spacer Location Dependent Duodenal Sparing and a Decision Support System for Spacer-Enabled Pancreatic Cancer Radiation Therapy.

Authors:  Hamed Hooshangnejad; Sina Youssefian; Amol Narang; Eun Ji Shin; Avani Dholakia Rao; Sarah Han-Oh; Todd McNutt; Junghoon Lee; Chen Hu; John Wong; Kai Ding
Journal:  Front Oncol       Date:  2022-03-24       Impact factor: 6.244

4.  Demonstrating the benefits of corrective intraoperative feedback in improving the quality of duodenal hydrogel spacer placement.

Authors:  Hamed Hooshangnejad; Sarah Han-Oh; Eun Ji Shin; Amol Narang; Avani Dholakia Rao; Junghoon Lee; Todd McNutt; Chen Hu; John Wong; Kai Ding
Journal:  Med Phys       Date:  2022-04-18       Impact factor: 4.506

5.  A new strategy for volumetric-modulated arc therapy planning using AutoPlanning based multicriteria optimization for nasopharyngeal carcinoma.

Authors:  Juanqi Wang; Zhi Chen; Weiwei Li; Wei Qian; Xiaosheng Wang; Weigang Hu
Journal:  Radiat Oncol       Date:  2018-05-16       Impact factor: 3.481

6.  A knowledge-based intensity-modulated radiation therapy treatment planning technique for locally advanced nasopharyngeal carcinoma radiotherapy.

Authors:  Penggang Bai; Xing Weng; Kerun Quan; Jihong Chen; Yitao Dai; Yuanji Xu; Fasheng Lin; Jing Zhong; Tianming Wu; Chuanben Chen
Journal:  Radiat Oncol       Date:  2020-08-03       Impact factor: 3.481

7.  Evaluation of Auto-Planning for Left-Side Breast Cancer After Breast-Conserving Surgery Based on Geometrical Relationship.

Authors:  Yijiang Li; Han Bai; Danju Huang; Feihu Chen; Yaoxiong Xia
Journal:  Technol Cancer Res Treat       Date:  2021 Jan-Dec
  7 in total

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