Tumor Volume Distributions Based on Weibull Distributions of Maximum Tumor Diameters

(1) Background: The distribution of tumor volumes is important for various aspects of cancer research. Unfortunately, tumor volume is rarely documented in tumor registries; usually only maximum tumor diameter is. This paper presents a method to derive tumor volume distributions from tumor diameter distributions. (2) Methods: The hypothesis is made that tumor maximum diameters d are Weibull distributed, and tumor volume is proportional to dk, where k is a parameter from the Weibull distribution of d. The assumption is tested by using a test dataset of 176 segmented tumor volumes and comparing the k obtained by fitting the Weibull distribution of d and from a direct fit of the volumes. Finally, tumor volume distributions are calculated from the maximum diameters of the SEER database for breast, NSCLC and liver. (3) Results: For the test dataset, the k values obtained from the two separate methods were found to be k = 2.14 ± 0.36 (from Weibull distribution of d) and 2.21 ± 0.25 (from tumor volume). The tumor diameter data from the SEER database were fitted to a Weibull distribution, and the resulting parameters were used to calculate the corresponding exponential tumor volume distributions with an average volume obtained from the diameter fit. (4) Conclusions: The agreement of the fitted k using independent data supports the presented methodology to obtain tumor volume distributions. The method can be used to obtain tumor volume distributions when only maximum tumor diameters are available

Tumour volume distribution can yield information on tumour growth and tumour control.

BACKGROUND It is shown that tumour volume distributions can yield information on two aspects of cancer research: tumour induction and tumour control. MATERIALS AND METHODS From the hypothesis that the intrinsic distribution of breast cancer volumes follows an exponential distribution, firstly the probability density function of tumour growth time was deduced via a mathematical transformation of the probability density functions of tumour volumes. In a second step, the distribution of tumour volumes was used to model the variation of the clonogenic cell number between patients in order to determine tumour control probabilities for radiotherapy patients. RESULTS Distribution of lag times, i.e. the time from the appearance of the first fully malignant cell until a clinically observable cancer, can be used to deduce the probability of tumour induction as a function of patient age. The integration of the volume variation with a Poisson-TCP model results in a logistic function which explains population-averaged survival data of radiotherapy patients. CONCLUSIONS The inclusion of tumour volume distributions into the TCP formalism enables a direct link to be deduced between a cohort TCP model (logistic) and a TCP model for individual patients (Poisson). The TCP model can be applied to non-uniform tumour dose distributions

A concept for anisotropic PTV margins including rotational setup uncertainties and its impact on the tumor control probability in canine brain tumors

Objective. In this modelling study, we pursued two main goals. The first was to establish a new CTV-to-PTV expansion which considers the closest and most critical organ at risk (OAR). The second goal was to investigate the impact of the planning target volume (PTV) margin size on the tumor control probability (TCP) and its dependence on the geometrical setup uncertainties. The aim was to achieve a smaller margin expansion close to the OAR while allowing a moderately larger expansion in less critical areas further away from the OAR and whilst maintaining the TCP. Approach. Imaging data of radiation therapy plans from pet dogs which had undergone radiation therapy for brain tumor were used to estimate the clinic specific rotational setup uncertainties. A Monte-Carlo methodology using a voxel-based TCP model was used to quantify the implications of rotational setup uncertainties on the TCP. A combination of algorithms was utilized to establish a computational CTV-to-PTV expansion method based on probability density. This was achieved by choosing a center of rotation close to an OAR. All required software modules were developed and integrated into a software package that directly interacts with the Varian Eclipse treatment planning system. Main results. Several uniform and non-isotropic PTVs were created. To ensure comparability and consistency, standardized RT plans with equal optimization constraints were defined, automatically applied and calculated on these targets. The resulting TCPs were then computed, evaluated and compared. Significance. The non-isotropic margins were found to result in larger TCPs with smaller margin excess volume. Further, we presented an additional application of the newly established CTV-to-PTV expansion method for radiation therapy of the spinal axis of human patients

The Impact of IMRT and Proton Radiotherapy on Secondary Cancer Incidence

Background and Purpose:: There is concern about the increase of radiation-induced malignancies with the application of modern radiation treatment techniques such as intensity-modulated radiotherapy (IMRT) and proton radiotherapy. Therefore, X-ray scatter and neutron radiation as well as the impact of the primary dose distribution on secondary cancer incidence are analyzed. Material and Methods:: The organ equivalent dose (OED) concept with a linear-exponential and a plateau dose-response curve was applied to dose distributions of 30 patients who received radiation therapy of prostate cancer. Three-dimensional conformal radiotherapy was used in eleven patients, another eleven patients received IMRT with 6-MV photons, and eight patients were treated with spot-scanned protons. The treatment plans were recalculated with 15-MV and 18-MV photons. Secondary cancer risk was estimated based on the OED for the different treatment techniques. Results:: A modest increase of 15% radiation-induced cancer results from IMRT using low energies (6 MV), compared to conventional four-field planning with 15-MV photons (plateau dose-response: 1%). The probability to develop a secondary cancer increases with IMRT of higher energies by 20% and 60% for 15 MV and 18 MV, respectively (plateau dose-response: 2% and 30%). The use of spot-scanned protons can reduce secondary cancer incidence as much as 50% (independent of dose-response). Conclusion:: By including the primary dose distribution into the analysis of radiation-induced cancer incidence, the resulting increase in risk for secondary cancer using modern treatment techniques such as IMRT is not as dramatic as expected from earlier studies. By using 6-MV photons, only a moderate risk increase is expected. Spot-scanned protons are the treatment of choice in regard to secondary cancer incidenc

Functional Analysis of Components Manufactured by a Sheet-Bulk Metal Forming Process

Due to rising demands regarding the functionality and load-bearing capacity of functional components such as synchronizer rings in gear systems, conventional forming operations are reaching their limits with respect to formability and efficiency. One way to meet these challenges is the application of the innovative process class of sheet-bulk metal forming (SBMF). By applying bulk forming operations to sheet metal, the advantages of both process classes can be combined, thus realizing an optimized part weight and an adapted load-bearing capacity. Different approaches to manufacturing relevant part geometries were presented and evaluated regarding the process properties and applicability. In this contribution, a self-learning engineering workbench was used to provide geometry-based data regarding a novel component geometry with circumferential involute gearing manufactured in an SBMF process combination of deep drawing and upsetting. Within the comprehensive investigations, the mechanical and geometrical properties of the part were analyzed. Moreover, the manufactured components were compared regarding the increased fatigue strength in cyclic load tests. With the gained experimental and numerical data, the workbench was used for the first time to generate the desired component as a CAD model, as well as to derive design guidelines referring to the investigated properties and fatigue behavior

Hypofractionated radiotherapy has the potential for second cancer reduction

<p>Abstract</p> <p>Background and Purpose</p> <p>A model for carcinoma and sarcoma induction was used to study the dependence of carcinogenesis after radiotherapy on fractionation.</p> <p>Materials and methods</p> <p>A cancer induction model for radiotherapy doses including fractionation was used to model carcinoma and sarcoma induction after a radiation treatment. For different fractionation schemes the dose response relationships were obtained. Tumor induction was studied as a function of dose per fraction.</p> <p>Results</p> <p>If it is assumed that the tumor is treated up to the same biologically equivalent dose it was found that large dose fractions could decrease second cancer induction. The risk decreases approximately linear with increasing fraction size and is more pronounced for sarcoma induction. Carcinoma induction decreases by around 10% per 1 Gy increase in fraction dose. Sarcoma risk is decreased by about 15% per 1 Gy increase in fractionation. It is also found that tissue which is irradiated using large dose fractions to dose levels lower than 10% of the target dose potentially develop less sarcomas when compared to tissues irradiated to all dose levels. This is not observed for carcinoma induction.</p> <p>Conclusions</p> <p>It was found that carcinoma as well as sarcoma risk decreases with increasing fractionation dose. The reduction of sarcoma risk is even more pronounced than carcinoma risk. Hypofractionation is potentially beneficial with regard to second cancer induction.</p

Track-event theory of cell survival with second-order repair

When fractionation schemes for hypofractionation and stereotactic body radiotherapy are considered, a reliable cell survival model at high dose is needed for calculating doses of similar biological effectiveness. In this work, a simple model for cell survival which is valid also at high dose is developed from Poisson statistics. It is assumed that a cell is killed by an event that is defined by two double-strand breaks on the same or different chromosomes. Two different mechanisms can produce events. A one-track event is always represented by two simultaneous double-strand breaks. A two-track event results in one double-strand break. Therefore, at least two two-track events on the same or different chromosomes are necessary to produce an event. It is assumed that two double-strand breaks can be repaired with a certain repair probability. Both the one-track events and the two-track events are statistically independent. From the stochastic nature of cell killing which is described by the Poisson distribution, the cell survival probability was derived. The model was fitted to experimental data. It was shown that a solution based on Poisson statistics exists for cell survival. It exhibits exponential cell survival at high dose and a finite gradient of cell survival at vanishing dose, which is in agreement with experimental cell studies. The model fits the experimental data as well as the LQ model and is based on two free parameters. It was shown that cell survival can be described with a simple analytical formula on the basis of Poisson statistics. This solution represents in the limit of large dose the typical exponential behavior and predicts cell survival as well as the LQ model

FIRE: A compact nanodosimeter detector based on ion amplification in gas

One goal of nanodosimetry is to determine statistical quantities of ionization distributions in nanometric volumes. It is hypothesized here that these quantities are related to the initial biological damages in DNA from ionizations. Thus nanodosimetric quantities will potentially complement or replace the concept of RBE-weighted absorbed dose and hence they could be applied in treatment planning systems, risk assessments for radiation protection and space radiation. The development of a compact and portable nanodosimeter detector available for clinical routine is a significant step towards that goal. We present extensive measurements to characterize the performance of the FIRE (Frequency of Ion REgistration) nanodosimeter detector. It operates on similar principles like the Gas Electron Multiplier (GEM). Contrary to GEMs the FIRE detector registers positive ions instead of electrons and operates at low pressures of 0.5 Torr to 2.5 Torr. In addition, the FIRE nanodosimeter capitalizes on the usage of a resistive cathode in order to suppress discharges. Moreover, the geometry of the FIRE detector is adapted to the low pressure by enlarging the typical dimensions of a GEM foil by two orders of magnitude. The authors present two configurations of the compact FIRE nanodosimetry detector. The resistivities of the two configurations differ by six orders of magnitude. The lower resistivity should allow for faster removal of the charges attached to the wall inside the hole channel. Measurements of mean number of ions produced by 5MeV alpha particles in low pressure propane gas, mean number of dark counts, the ion arrival time, and the mean avalanche charge are presented. The dependency of these parameters on acceleration voltage, drift voltage, pressure and hole diameter were investigated

A model of radiation action based on nanodosimetry and the application to ultra-soft X-rays

A radiation action model based on nanodosimetry is presented. It is motivated by the finding that the biological effects of various types of ionizing radiation lack a consistent relation with absorbed dose. It is postulated that the common fundamental cause of these effects is the production of elementary sublesions (DSB), which are created at a rate that is proportional to the probability to produce more than two ionisations within a volume of 10 base pairs of the DNA. The concepts of nanodosimetry allow for a quantitative characterization of this process in terms of the cumulative probability F2. The induced sublesions can interact in two ways to produce lethal damage. First, if two or more sublesions accumulate in a locally limited spherical volume of 3–10 nm in diameter, clustered DNA damage is produced. Second, consequent interactions or rearrangements of some of the initial damage over larger distances (~ µm) can produce additional lethal damage. From the comparison of theoretical predictions deduced from this concept with experimental data on relative biological effectiveness, a cluster volume with a diameter of 7.5 nm could be determined. It is shown that, for electrons, the predictions agree well with experimental data over a wide energy range. The only free parameter needed to model cell survival is the intersection cross-section which includes all relevant cell-specific factors. Using ultra-soft X-rays it could be shown that the energy dependence of cell survival is directly governed by the nanodosimetric characteristics of the radiation track structure. The cell survival model derived in this work exhibits exponential cell survival at a high dose and a finite gradient of cell survival at vanishing dose, as well as the dependence on dose-rate