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Title: SU-F-J-187: The Statistical NTCP and TCP Models in the Proton Therapy

Abstract

Purpose: The statistical models (SM) are typically used as a subjective description of a population for which there is only limited sample data, and especially in cases where the relationship between variables is known. The normal tissue complications and tumor control are frequently stochastic effects in the Radiotherapy (RT). Based on probabilistic treatments, it recently has been formulated new NTCP and TCP models for the RT. Investigating the particular requirements for their clinical use in the proton therapy (PT) is the goal of this work. Methods: The SM can be used as phenomenological or mechanistic models. The former way allows fitting real data and getting theirparameters. In the latter one, we should do efforts for determining the parameters through the acceptable estimations, measurements, and/or simulation experiments. Experimental methodologies for determination of the parameters have been developed from the fraction cells surviving the proton irradiation curves in tumor and OAR, and precise RBE models are used for calculating the variable of effective dose. As the executions of these methodologies have a high costs, so we have developed computer tools enable to perform simulation experiments as complement to limitations of the real ones. Results: The requirements for the use of the SMmore » in the PT, such as validation and improvement of the elaborated and existent methodologies for determining the SM parameters and effective dose respectively, were determined. Conclusion: The SM realistically simulates the main processes in the PT, and for this reason these can be implemented in this therapy, which are simples, computable and they have other advantages over some current models. It has been determined some negative aspects for some currently used probabilistic models in the RT, like the LKB NTCP and others derived from logistic functions; which can be improved with the proposed methods in this study.« less

Authors:
 [1];  [2];  [3];  [4];  [5];  [6];  [7]
  1. Princeton Radiation Oncology, Princeton Radiation Oncology (United States)
  2. Theoretical and Computational Methods Working Group of IMAG, Santiago de Cuba (Cuba)
  3. National Cancer Institute, Rockville, MD (United States)
  4. MD Anderson Cancer Center, Houston, TX (United States)
  5. Northwestern University, Chicago, IL (United States)
  6. Provincial Hospital of Santiago de Cuba, Santiago de Cuba (Cuba)
  7. Faculty of Electrics of the University of Oriente, Santiago de Cuba (Cuba)
Publication Date:
OSTI Identifier:
22634783
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ANIMAL TISSUES; COMPLEMENT; IRRADIATION; NEOPLASMS; PROBABILISTIC ESTIMATION; PROTON BEAMS; RADIATION DOSES; RADIOTHERAPY; SIMULATION; STOCHASTIC PROCESSES; VALIDATION

Citation Formats

Jang, S, Frometa, T, Pyakuryal, A, Sio, T, Piseaux, R, Acosta, S, and Ocana, K. SU-F-J-187: The Statistical NTCP and TCP Models in the Proton Therapy. United States: N. p., 2016. Web. doi:10.1118/1.4956095.
Jang, S, Frometa, T, Pyakuryal, A, Sio, T, Piseaux, R, Acosta, S, & Ocana, K. SU-F-J-187: The Statistical NTCP and TCP Models in the Proton Therapy. United States. doi:10.1118/1.4956095.
Jang, S, Frometa, T, Pyakuryal, A, Sio, T, Piseaux, R, Acosta, S, and Ocana, K. Wed . "SU-F-J-187: The Statistical NTCP and TCP Models in the Proton Therapy". United States. doi:10.1118/1.4956095.
@article{osti_22634783,
title = {SU-F-J-187: The Statistical NTCP and TCP Models in the Proton Therapy},
author = {Jang, S and Frometa, T and Pyakuryal, A and Sio, T and Piseaux, R and Acosta, S and Ocana, K},
abstractNote = {Purpose: The statistical models (SM) are typically used as a subjective description of a population for which there is only limited sample data, and especially in cases where the relationship between variables is known. The normal tissue complications and tumor control are frequently stochastic effects in the Radiotherapy (RT). Based on probabilistic treatments, it recently has been formulated new NTCP and TCP models for the RT. Investigating the particular requirements for their clinical use in the proton therapy (PT) is the goal of this work. Methods: The SM can be used as phenomenological or mechanistic models. The former way allows fitting real data and getting theirparameters. In the latter one, we should do efforts for determining the parameters through the acceptable estimations, measurements, and/or simulation experiments. Experimental methodologies for determination of the parameters have been developed from the fraction cells surviving the proton irradiation curves in tumor and OAR, and precise RBE models are used for calculating the variable of effective dose. As the executions of these methodologies have a high costs, so we have developed computer tools enable to perform simulation experiments as complement to limitations of the real ones. Results: The requirements for the use of the SM in the PT, such as validation and improvement of the elaborated and existent methodologies for determining the SM parameters and effective dose respectively, were determined. Conclusion: The SM realistically simulates the main processes in the PT, and for this reason these can be implemented in this therapy, which are simples, computable and they have other advantages over some current models. It has been determined some negative aspects for some currently used probabilistic models in the RT, like the LKB NTCP and others derived from logistic functions; which can be improved with the proposed methods in this study.},
doi = {10.1118/1.4956095},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = {Wed Jun 15 00:00:00 EDT 2016},
month = {Wed Jun 15 00:00:00 EDT 2016}
}
  • Purpose: To utilize online CBCT scans to develop models for predicting DVH metrics in proton therapy of head and neck tumors. Methods: Nine patients with locally advanced oropharyngeal cancer were retrospectively selected in this study. Deformable image registration was applied to the simulation CT, target volumes, and organs at risk (OARs) contours onto each weekly CBCT scan. Intensity modulated proton therapy (IMPT) treatment plans were created on the simulation CT and forward calculated onto each corrected CBCT scan. Thirty six potentially predictive metrics were extracted from each corrected CBCT. These features include minimum/maximum/mean over and under-ranges at the proximal andmore » distal surface of PTV volumes, and geometrical and water equivalent distance between PTV and each OARs. Principal component analysis (PCA) was used to reduce the dimension of the extracted features. Three principal components were found to account for over 90% of variances in those features. Datasets from eight patients were used to train a machine learning model to fit these principal components with DVH metrics (dose to 95% and 5% of PTV, mean dose or max dose to OARs) from the forward calculated dose on each corrected CBCT. The accuracy of this model was verified on the datasets from the 9th patient. Results: The predicted changes of DVH metrics from the model were in good agreement with actual values calculated on corrected CBCT images. Median differences were within 1 Gy for most DVH metrics except for larynx and constrictor mean dose. However, a large spread of the differences was observed, indicating additional training datasets and predictive features are needed to improve the model. Conclusion: Intensity corrected CBCT scans hold the potential to be used for online verification of proton therapy and prediction of delivered dose distributions.« less
  • Purpose: To report an approach to quantify the normal tissue sparing for 4D robustly-optimized versus PTV-optimized IMPT plans. Methods: We generated two sets of 90 DVHs from a patient’s 10-phase 4D CT set; one by conventional PTV-based optimization done in the Eclipse treatment planning system, and the other by an in-house robust optimization algorithm. The 90 DVHs were created for the following scenarios in each of the ten phases of the 4DCT: ± 5mm shift along x, y, z; ± 3.5% range uncertainty and a nominal scenario. A Matlab function written by Gay and Niemierko was modified to calculate EUDmore » for each DVH for the following structures: esophagus, heart, ipsilateral lung and spinal cord. An F-test determined whether or not the variances of each structure’s DVHs were statistically different. Then a t-test determined if the average EUDs for each optimization algorithm were statistically significantly different. Results: T-test results showed each structure had a statistically significant difference in average EUD when comparing robust optimization versus PTV-based optimization. Under robust optimization all structures except the spinal cord received lower EUDs than PTV-based optimization. Using robust optimization the average EUDs decreased 1.45% for the esophagus, 1.54% for the heart and 5.45% for the ipsilateral lung. The average EUD to the spinal cord increased 24.86% but was still well below tolerance. Conclusion: This work has helped quantify a qualitative relationship noted earlier in our work: that robust optimization leads to plans with greater normal tissue sparing compared to PTV-based optimization. Except in the case of the spinal cord all structures received a lower EUD under robust optimization and these results are statistically significant. While the average EUD to the spinal cord increased to 25.06 Gy under robust optimization it is still well under the TD50 value of 66.5 Gy from Emami et al. Supported in part by the NCI U19 CA021239.« less
  • Purpose: To estimate the radiobiological parameters of four NTCP models that describe the dose-response relations of pharyngeal constrictors and proximal esophagus regarding the severity of patient reported swallowing problems 6 months post chemo-radiotherapy. To identify the section/structure that best correlates with the manifestation of the clinical endpoints. Finally, to compare the goodness-of-fit of those models. Methods: Forty-three patients were treated on a prospective multi-institutional phase II study for oropharyngeal squamous cell carcinoma. All the patients received 60 Gy IMRT and they reported symptoms using the novel patient reported outcome version of the CTCAE. We derived the individual patient dosimetric datamore » of superior, medium and inferior sections of pharyngeal constrictors (SPC, MPC and IPC), superior and inferior sections of esophagus (SES and IES) as separate structures as well as combinations. The Lyman-Kutcher-Burman (LKB), Relative Seriality (RS), Logit and Relative Logit (RL) NTCP models were used to fit the patient data. The fitting of the different models was assessed through the area under the receiver operating characteristic curve (AUC) and the Odds Ratio methods. Results: The AUC values were highest for the SPC for Grade ≥ 2 (0.719 for the RS and RL models, and 0.716 for LKB and Logit). For Grade ≥ 1, the respective values were 0.699 for RS, LKB and Logit and 0.676 for RL. For MPC the AUC values varied between 0.463–0.477, for IPC between 0.396–0.458, for SES between 0.556–0.613 and for IES between 0.410–0.519. The Odds Ratio for the SPC was 15.6 (1.7–146.4) for RS, LKB and Logit for NTCP of 55%. Conclusion: All the examined NTCP models could fit the clinical data with similar accuracy. The SPC appear to correlate best with the clinical endpoints of swallowing problems. A prospective study could establish the use of NTCP values of SPC as a constraint in treatment planning.« less
  • Purpose: To estimate the radiobiological parameters of four popular NTCP models that describe the dose-response relations of salivary glands to the severity of patient reported dry mouth 6 months post chemo-radiotherapy. To identify the glands, which best correlate with the manifestation of those clinical endpoints. Finally, to evaluate the goodness-of-fit of the NTCP models. Methods: Forty-three patients were treated on a prospective multiinstitutional phase II study for oropharyngeal squamous cell carcinoma. All the patients received 60 Gy IMRT and they reported symptoms using the novel patient reported outcome version of the CTCAE. We derived the individual patient dosimetric data ofmore » the parotid and submandibular glands (SMG) as separate structures as well as combinations. The Lyman-Kutcher-Burman (LKB), Relative Seriality (RS), Logit and Relative Logit (RL) NTCP models were used to fit the patients data. The fitting of the different models was assessed through the area under the receiver operating characteristic curve (AUC) and the Odds Ratio methods. Results: The AUC values were highest for the contralateral parotid for Grade ≥ 2 (0.762 for the LKB, RS, Logit and 0.753 for the RL). For the salivary glands the AUC values were: 0.725 for the LKB, RS, Logit and 0.721 for the RL. For the contralateral SMG the AUC values were: 0.721 for LKB, 0.714 for Logit and 0.712 for RS and RL. The Odds Ratio for the contralateral parotid was 5.8 (1.3–25.5) for all the four NTCP models for the radiobiological dose threshold of 21Gy. Conclusion: It was shown that all the examined NTCP models could fit the clinical data well with very similar accuracy. The contralateral parotid gland appears to correlated best with the clinical endpoints of severe/very severe dry mouth. An EQD2Gy dose of 21Gy appears to be a safe threshold to be used as a constraint in treatment planning.« less
  • Purpose: To to determine if tumor control probability (TCP) and normal tissue control probability (NTCP) values computed on the treatment planning image are representative of TCP/NTCP distributions resulting from probable positioning variations encountered during external-beam radiotherapy. Methods: We compare TCP/NTCP as typically computed on the planning PTV/OARs with distributions of those parameters computed for CTV/OARs via treatment delivery simulations which include the effect of patient organ deformations for a group of 19 prostate IMRT pseudocases. Planning objectives specified 78 Gy to PTV1=prostate CTV+5 mm margin, 66 Gy to PTV2=seminal vesicles+8 mm margin, and multiple bladder/rectum OAR objectives to achieve typicalmore » clinical OAR sparing. TCP were computed using the Poisson Model while NTCPs used the Lyman-Kutcher-Bruman model. For each patient, 1000 30-fraction virtual treatment courses were simulated with each fractional pseudo- time-oftreatment anatomy sampled from a principle component analysis patient deformation model. Dose for each virtual treatment-course was determined via deformable summation of dose from the individual fractions. CTVTCP/ OAR-NTCP values were computed for each treatment course, statistically analyzed, and compared with the planning PTV-TCP/OARNTCP values. Results: Mean TCP from the simulations differed by <1% from planned TCP for 18/19 patients; 1/19 differed by 1.7%. Mean bladder NTCP differed from the planned NTCP by >5% for 12/19 patients and >10% for 4/19 patients. Similarly, mean rectum NTCP differed by >5% for 12/19 patients, >10% for 4/19 patients. Both mean bladder and mean rectum NTCP differed by >5% for 10/19 patients and by >10% for 2/19 patients. For several patients, planned NTCP was less than the minimum or more than the maximum from the treatment course simulations. Conclusion: Treatment course simulations yield TCP values that are similar to planned values, while OAR NTCPs differ significantly, indicating the need for probabilistic methods or PRVs for OAR risk assessment. Presenting author receives support from Philips Medical Systems.« less