The use of the normal tissue non-complication probability (NTCP0) in the safety evaluations as a new alternative of assessing the side-effects of the radiation oncology treatments.

PURPOSE: To encourage the use of the NTCP0 for evaluating safety as a new alternative of assessing the S-Es of the radiation oncology treatments; and the use of the 'NTCP0cal' methodology that calculates/estimates NTCP0. METHOD: Revisions of studies related to use of the NTCP in the evaluations of S-Es. Development of the first version of the Matlab application of our methodology, which provides three options, two of them employ the well-known aspects of a phenomenological model, or the relationship with the TNTCP; where NTCP0 = 100%-TNTCP; and the third option determines NTCP0 from an assumed NTCP discrete probabilistic distribution from the binomial distribution, where one of its parameters is automatically defined from a databased of the Disease locations Vs. Late complications. RESULT: As result of revisions of some QUANTEC studies, we can say that: (1) The majority of current NTCP models are DVH-based; (2) The risk of toxicity is the way of evaluating the S-Es of the radiation oncology treatments; and (3) The NTCP are used mainly for evaluations of individual or principal complications or Endpoints of the radiation treatments. The 'NTCP0cal' Matlab application developed in this study has three calculation options. Two of the options provide additional graphical information about the distributions. CONCLUSIONS: The NTCP0 is a new radiobiological concept, its introduction let to correct some current P + and UTCP formulations, and will allow evaluating S-Es in whatever activity involving ionizing radiation, like radiation treatments; and its phenomenological model function of dose prescribed (D = n*d) will allow calculating values of NTCP0 for a range of dose per fraction (d) in a treatment with a determined number of fractions (n), or for range of n for a constant d. The DVH is irrelevant for this model. For whatever radiation treatment given to a population of similar patients under similar circumstances, the NTCP0 is calculated as ratio of the number of patients without acute/late complications and total of them. When this number is unknown, then NTCP0 can be obtained using the 'NTCP0cal' application.

The use of the normal tissue non-complication probability (NTCP0) methodology as a new alternative of assessing side-effects in brachytherapy treatments.

Background: The NTCP methodology evaluating side-effects (S-Es) was initially used in radiotherapy (RT), and later was extended to brachytherapy (BT). The NTCP0 methodology has been recently introduced in RT. Given the advantages, this methodology could replace NTCP. Materials and methods: Revisions of studies related to use of NTCP in the evaluations of S-Es in BT. Development of the first versions of two Matlab applications of the NTCP0 methodology. These applications have three options. Two of them employ the well-known aspects of a phenomenological model, or the probabilistic relationship between NTCP0 and total NTCP (TNTCP) that is the sum(NTCP(x i )) i: i th complication i:1..nc: Number of complications; where NTCP0 = 100% - TNTCP; and the third option assumes a NTCP(xi) discrete probabilistic distribution generated by the binomial distribution, where one of its parameters is automatically obtained from a databased of the Disease locations Vs. Late complications. Results: The NTCP0cal and NTCP0calDr Matlab applications have been developed, and respectively used for fractional continuous low dose-rate BT. Conclusions: NTCP0 is defined as the ratio of the number of patients without acute/late complications and total of them, and also can be obtained using our Matlab applications. NTCP0 works do not disregard the last 10-15 years of NTCP research; but NTCP0 was not considered during these years. A generic example was used for showing the variations of the late complications and NTCP0 for a BT treatment of a constant number of fractions and six different dose per fraction values.

Proposals of models for new formulations of the current complication-free cure (P+) and uncomplicated tumor control probability (UTCP) concepts, and total normal tissue complication probability of late complications.

This study proposes phenomenological models for total normal tissue complication probability (TNTCP) and NTCP0. NTCP0 is a new acronym for reformulating the current complication-free cure (P+) and uncomplicated tumor control probability (UTCP) concepts, and TNTCP will reformulate the current NTCP involving multiple organs at risks. The current probabilistic concepts are incoherently formulated with mathematical operations of tumor control probability (TCP) and normal tissue complication probability (NTCP) that are associated with different stochastic processes and random variables. NTCP0 is equal to NTCP0 (normal tissue non-complication probability) that is calculated as the ratio of a number of patients of a population without late complications and a total of them. As a cumulative distribution function (CDF) of late complications, TNTCP = sum(NTCPi), where NTCPi is the NTCP of the ith late complication. TNTCP is also a new acronym, and the probabilistic complement of NTCP0, then NTCP0 = 100% - TNTCP. The NTCP0/TNTCP (D(d)) proposing models are based on the relationship between the NTCP0/TNTCP and total dose (D = n×d; where d = dose per fraction, and n = number of fractions). TNTCP(D) model will be correlated with LKB model (the normal CDF) that is an increasing function; and NTCP0(D) model with a decreasing function, which additionally will define clear limits of three possible regions for NTCP0: 0 and 100% deterministic, and a stochastic. These models are function D, which is widely used for characterizing radiation therapies.

Physical and Radiobiological Evaluation of Accelerated Intensity Modulated Radiotherapy for Locally Advanced Head and Neck Cancer and Comparison with Short-Term Clinical Outcomes.

Objective: The present study aims to evaluate the accelerated intensity modulated radiotherapy (IMRT) of head and neck (HandN) treatments using physical indices and radiobiological models with its clinical correlation using histogram analysis in radiation therapy (HART). The radiobiological evaluation in terms of tumor control probability (TCP) and normal tissue complication probability (NTCP) indices were compared with acute toxicity. Materials and Methods: A total of twenty patients with stage III and IV of HandN cases treated with accelerated IMRT using 6MV photons were chosen for the study. Using HART software, physical indices of the IMRT plans have been defined by universal plan indices (UPI's) which summarize the various recognized plan indices. The overall quality factor (QF) of a plan was determined by a linear combination of all indices in UPI set. The clinical outcomes in terms of the acute toxicity like dysphagia and xerostomia were compared with NTCP values of the OAR calculated from HART software. Results: The mean QF and the mean Poisson TCP index was found to be 0.993±0.02 and 0.86 ±0.02 respectively. The mean JT Lyman NTCP index for bilateral parotid, constrictors, and larynx were found to be 0.23±0.14, 0.30±0.17 and 0.22±0.15 respectively. The acute toxicities in terms of severity of xerostomia and dysphagia have shown a moderate correlation with NTCP values of bilateral parotids, constrictors, and larynx, respectively. Conclusion: The mean QF based on UPI was found to be close to unity, which correlates with being a better IMRT plan. The present study suggested the existence of a moderate correlation between the calculated NTCP values and their respective severities of the organ at risk (OAR's). Accelerated IMRT with chemotherapy is a clinically feasible option in the treatment of locally advanced head and neck squamous cell carcinoma (HNSCC) with encouraging initial tumor response and acceptable acute toxicities.

Conversion of computational human phantoms into DICOM-RT for normal tissue dose assessment in radiotherapy patients.

Radiotherapy (RT) treatment planning systems (TPS) are designed for the fast calculation of dose to the tumor bed and nearby organs at risk using x-ray computed tomography (CT) images. However, CT images for a patient are typically available for only a small portion of the body, and in some cases, such as for retrospective epidemiological studies, no images may be available at all. When dose to organs that lie out-of-scan must be estimated, a convenient alternative for the unknown patient anatomy is to use a matching whole-body computational phantom as a surrogate. The purpose of the current work is to connect such computational phantoms to commercial RT TPS for retrospective organ dose estimation. A custom software with graphical user interface (GUI), called the DICOM-RT Generator, was developed in MATLAB to convert voxel computational phantoms into the digital imaging and communications in medicine radiotherapy (DICOM-RT) format, compatible with commercial TPS. DICOM CT image sets for the phantoms are created via a density-to-Hounsfield unit (HU) conversion curve. Accompanying structure sets containing the organ contours are automatically generated by tracing binary masks of user-specified organs on each phantom CT slice. The software was tested on a library of body size-dependent phantoms, the International Commission on Radiological Protection reference phantoms, and a canine voxel phantom, taking only a few minutes per conversion. The resulting DICOM-RT files were tested on several commercial TPS. As an example application, a library of converted phantoms was used to estimate organ doses for members of the National Wilms Tumor Study (NWTS) cohort. The converted phantom library, in DICOM format, and a standalone MATLAB-compiled executable of the DICOM-RT Generator are available for others to use for research purposes (http://ncidose.cancer.gov).

Dosimetric and radiobiological comparison for quality assurance of IMRT and VMAT plans.

INTRODUCTION: The gamma analysis used for quality assurance of a complex radiotherapy plan examines the dosimetric equivalence between planned and measured dose distributions within some tolerance. This study explores whether the dosimetric difference is correlated with any radiobiological difference between delivered and planned dose. METHODS: VMAT or IMRT plans optimized for 14 cancer patients were calculated and delivered to a QA device. Measured dose was compared against planned dose using 2-D gamma analysis. Dose volume histograms (for various patient structures) obtained by interpolating measured data were compared against the planned ones using a 3-D gamma analysis. Dose volume histograms were used in the Poisson model to calculate tumor control probability for the treatment targets and in the Sigmoid dose-response model to calculate normal tissue complication probability for the organs at risk. RESULTS: Differences in measured and planned dosimetric data for the patient plans passing at ≥94.9% rate at 3%/3 mm criteria are not statistically significant. Average ± standard deviation tumor control probabilities based on measured and planned data are 65.8±4.0% and 67.8±4.1% for head and neck, and 71.9±2.7% and 73.3±3.1% for lung plans, respectively. The differences in tumor control probabilities obtained from measured and planned dose are statistically insignificant. However, the differences in normal tissue complication probabilities for larynx, lungs-GTV, heart, and cord are statistically significant for the patient plans meeting ≥94.9% passing criterion at 3%/3 mm. CONCLUSION: A ≥90% gamma passing criterion at 3%/3 mm cannot assure the radiobiological equivalence between planned and delivered dose. These results agree with the published literature demonstrating the inadequacy of the criterion for dosimetric QA and suggest for a tighter tolerance.

Reconstruction of organ dose for external radiotherapy patients in retrospective epidemiologic studies.

Organ dose estimation for retrospective epidemiological studies of late effects in radiotherapy patients involves two challenges: radiological images to represent patient anatomy are not usually available for patient cohorts who were treated years ago, and efficient dose reconstruction methods for large-scale patient cohorts are not well established. In the current study, we developed methods to reconstruct organ doses for radiotherapy patients by using a series of computational human phantoms coupled with a commercial treatment planning system (TPS) and a radiotherapy-dedicated Monte Carlo transport code, and performed illustrative dose calculations. First, we developed methods to convert the anatomy and organ contours of the pediatric and adult hybrid computational phantom series to Digital Imaging and Communications in Medicine (DICOM)-image and DICOM-structure files, respectively. The resulting DICOM files were imported to a commercial TPS for simulating radiotherapy and dose calculation for in-field organs. The conversion process was validated by comparing electron densities relative to water and organ volumes between the hybrid phantoms and the DICOM files imported in TPS, which showed agreements within 0.1 and 2%, respectively. Second, we developed a procedure to transfer DICOM-RT files generated from the TPS directly to a Monte Carlo transport code, x-ray Voxel Monte Carlo (XVMC) for more accurate dose calculations. Third, to illustrate the performance of the established methods, we simulated a whole brain treatment for the 10 year-old male phantom and a prostate treatment for the adult male phantom. Radiation doses to selected organs were calculated using the TPS and XVMC, and compared to each other. Organ average doses from the two methods matched within 7%, whereas maximum and minimum point doses differed up to 45%. The dosimetry methods and procedures established in this study will be useful for the reconstruction of organ dose to support retrospective epidemiological studies of late effects in radiotherapy patients.

Comparing gamma knife and cyberknife in patients with brain metastases.

The authors compared the relative dosimetric merits of Gamma Knife (GK) and CyberKnife (CK) in 15 patients with 26 brain metastases. All patients were initially treated with the Leksell GK 4C. The same patients were used to generate comparative CK treatment plans. The tissue volume receiving more than 12 Gy (V12), the difference between V12 and tumor volume (V12net), homogeneity index (HI), and gradient indices (GI25, GI50) were calculated. Peripheral dose falloff and three conformity indices were compared. The median tumor volume was 2.50 cm3 (range, 0.044-19.9). A median dose of 18 Gy (range, 15-22) was prescribed. In GK and CK plans, doses were prescribed to the 40-50% and 77-92% isodose lines, respectively. Comparing GK to CK, the respective parametric values (median ± standard deviation) were: minimum dose (18.2 ± 3.4 vs. 17.6 ± 2.4 Gy, p = 0.395); mean dose (29.6 ± 5.1 vs. 20.6 ± 2.8 Gy, p < 0.00001); maximum dose (40.3 ± 6.5 vs. 22.7 ± 3.3 Gy, p < 0.00001); and HI (2.22 ± 0.19 vs. 1.18 ± 0.06, p < 0.00001). The median dosimetric indices (GK vs. CK, with range) were: RTOG_CI, 1.76 (1.12-4.14) vs. 1.53 (1.16-2.12), p = 0.0220; CI, 1.76 (1.15-4.14) vs. 1.55 (1.18-2.21), p = 0.050; nCI, 1.76 (1.59-4.14) vs. 1.57 (1.20-2.30), p = 0.082; GI50, 2.91 (2.48-3.67) vs. 4.90 (3.42-11.68), p < 0.00001; GI25, 6.58 (4.18-10.20) vs. 14.85 (8.80-48.37), p < 0.00001. Average volume ratio (AVR) differences favored GK at multiple normalized isodose levels (p < 0.00001). We concluded that in patients with brain metastases, CK and GK resulted in dosimetrically comparable plans that were nearly equivalent in several metrics, including target coverage and minimum dose within the target. Compared to GK, CK produced more homogenous plans with significantly lower mean and maximum doses, and achieved more conformal plans by RTOG_CI criteria. By GI and AVR analyses, GK plans had sharper peripheral dose falloff in most cases.

A computational tool for the efficient analysis of dose-volume histograms from radiation therapy treatment plans.

A Histogram Analysis in Radiation Therapy (HART) program was primarily developed to increase the efficiency and accuracy of dose-volume histogram (DVH) analysis of large quantities of patient data in radiation therapy research. The program was written in MATLAB to analyze patient plans exported from the treatment planning system (Pinnacle 3 ) in the American Association of Physicists in Medicine/Radiation Therapy Oncology Group (AAPM/RTOG) format. HART-computed DVH data was validated against manually extracted data from the planning system for five head and neck cancer patients treated with the intensity-modulated radiation therapy (IMRT) technique. HART calculated over 4000 parameters from the differential DVH (dDVH) curves for each patient in approximately 10-15 minutes. Manual extraction of this amount of data required 5 to 6 hours. The normalized root mean square deviation (NRMSD) for the HART-extracted DVH outcomes was less than 1%, or within 0.5% distance-to-agreement (DTA). This tool is supported with various user-friendly options and graphical displays. Additional features include optimal polynomial modeling of DVH curves for organs, treatment plan indices (TPI) evaluation, plan-specific outcome analysis (POA), and spatial DVH (zDVH) and dose surface histogram (DSH) analyses, respectively. HART is freely available to the radiation oncology community.