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

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

Risk adaptive planning with biology-based constraints may lead to higher tumor control probability in tumors of the canine brain: A planning study

Background: Classical radiation protocols are guided by physical dose delivered homogeneously over the target. Protocols are chosen to keep normal tissue complication probability (NTCP) at an acceptable level. Organs at risk (OAR) adjacent to the target volume could lead to underdosage of the tumor and a decrease of tumor control probability (TCP). The intent of our study was to explore a biology-based dose escalation: by keeping NTCP for OAR constant, radiation dose was to be maximized, allowing to result in heterogeneous dose distributions. Methods: We used computed tomography datasets of 25 dogs with brain tumors, previously treated with 10x4 Gy (40 Gy to PTV D50). We generated 3 plans for each patient: A) original treatment plan with homogeneous dose distribution, B) heterogeneous dose distribution with strict adherence to the same NTCPs as in A), and C) heterogeneous dose distribution with adherence to NTCP <5%. For plan comparison, TCPs and TCP equivalent doses (homogenous target dose which results in the same TCP) were calculated. To enable the use of the generalized equivalent uniform dose (gEUD) metric of the tumor target in plan optimization, the calculated TCP values were used to obtain the volume effect parameter a. Results: As intended, NTCPs for all OARs did not differ from plan A) to B). In plan C), however, NTCPs were significantly higher for brain (mean 2.5% (SD±1.9, 95%CI: 1.7,3.3), p<0.001), optic chiasm (mean 2.0% (SD±2.2, 95%CI: 1.0,2.8), p=0.010) compared to plan A), but no significant increase was found for the brainstem. For 24 of 25 of the evaluated patients, the heterogenous plans B) and C) led to an increase in target dose and projected increase in TCP compared to the homogenous plan A). Furthermore, the distribution of the projected individual TCP values as a function of the dose was found to be in good agreement with the population TCP model. Conclusion: Our study is a first step towards risk-adaptive radiation dose optimization. This strategy utilizes a biologic objective function based on TCP and NTCP instead of an objective function based on physical dose constraints. Keywords: Biologic objective function; Biology-based; Brain tumor; Dog; IMRT; Intensity-modulated radiation therapy; NTCP; Radiation therapy; Risk-adaptive optimization; TCP

Synopse virologischer Analysen im Nationalen Referenzzentrum für Influenzaviren während der COVID-19-Pandemie

Das Nationale Referenzzentrum für Influenzaviren gewinnt durch die fortlaufende Untersuchung von Proben aus den Sentinelpraxen der Arbeitsgemeinschaft Influenza einen umfassenden Überblick über die zirkulierenden respiratorischen Erreger in Deutschland. Dazu gehören neben SARS-CoV-2 und den Influenzaviren auch das Respiratorische Synzytialvirus, Parainfluenzaviren, humane Metapneumoviren, humane saisonale Coronaviren und humane Rhinoviren. Die Analyseergebnisse von 15.660 Sentinelproben sowie weiteren Isolaten im Zeitraum von Kalenderwoche 5/2020 bis 21/2022 werden im Epidemiologischen Bulletin 22/2022 vorgestellt. Beschrieben werden außerdem die Zirkulation respiratorischer Erreger im Vergleich zu vorpandemischen Saisons, die molekulare Charakterisierung und phylogenetische Analysen, die Überprüfung der Passgenauigkeit der eingesetzten Influenzaimpfstoffe und die Resistenzprüfung von Influenzaviren

Complete patient exposure during paediatric brain cancer treatment for photon and proton therapy techniques including imaging procedures

BackgroundIn radiotherapy, especially when treating children, minimising exposure of healthy tissue can prevent the development of adverse outcomes, including second cancers. In this study we propose a validated Monte Carlo framework to evaluate the complete patient exposure during paediatric brain cancer treatment.Materials and methodsOrgan doses were calculated for treatment of a diffuse midline glioma (50.4 Gy with 1.8 Gy per fraction) on a 5-year-old anthropomorphic phantom with 3D-conformal radiotherapy, intensity modulated radiotherapy (IMRT), volumetric modulated arc therapy (VMAT) and intensity modulated pencil beam scanning (PBS) proton therapy. Doses from computed tomography (CT) for planning and on-board imaging for positioning (kV-cone beam CT and X-ray imaging) accounted for the estimate of the exposure of the patient including imaging therapeutic dose. For dose calculations we used validated Monte Carlo-based tools (PRIMO, TOPAS, PENELOPE), while lifetime attributable risk (LAR) was estimated from dose-response relationships for cancer induction, proposed by Schneider et al.ResultsOut-of-field organ dose equivalent data of proton therapy are lower, with doses between 0.6 mSv (testes) and 120 mSv (thyroid), when compared to photon therapy revealing the highest out-of-field doses for IMRT ranging between 43 mSv (testes) and 575 mSv (thyroid). Dose delivered by CT ranged between 0.01 mSv (testes) and 72 mSv (scapula) while a single imaging positioning ranged between 2 μSv (testes) and 1.3 mSv (thyroid) for CBCT and 0.03 μSv (testes) and 48 μSv (scapula) for X-ray. Adding imaging dose from CT and daily CBCT to the therapeutic demonstrated an important contribution of imaging to the overall radiation burden in the course of treatment, which is subsequently used to predict the LAR, for selected organs.ConclusionThe complete patient exposure during paediatric brain cancer treatment was estimated by combining the results from different Monte Carlo-based dosimetry tools, showing that proton therapy allows significant reduction of the out-of-field doses and secondary cancer risk in selected organs

Mathematical modelling of tumor control in the context of radiation therapy with deliberate heterogeneous dose distributions

Contents Acknowledgements 3 Preamble 5 1 Background & Motivation 2 Summary & Conclusions Publications I A novel analytical population TCP model includes cell density and volume variations: application to canine brain tumor II A concept for anisotropic PTV margins including rotational setup uncertainties and its impact on the tumor control probability in canine brain tumors III Risk adaptive planning with biology-based constraints leads to higher tumor control probability in tumors of the canine brain: a planning study IV Mathematical modelling of the distribution of tumor size in patient population

Investigation of the effect of air gap size on the spatial resolution in proton- and helium radio- and tomography

Proton computed (transmission) tomography (pCT) refers to the process of imaging an object by letting protons pass through it, while measuring their energy after, and their position and (optionally) direction both before and after their traversal through that object. The so far experimental technique has potential to improve treatment planning of proton therapy by enabling the direct acquisition of a proton stopping power map of tissue, thus removing the need to obtain it by converting X-ray CT attenuation data and thereby eliminating uncertainties which arise in the mentioned conversion process. The image reconstruction in pCT requires accurate estimates of the proton trajectories. In experimental pCT detector setups where the direction of the protons is not measured, the air gap between the detector planes and the imaged object worsens the spatial resolution of the image obtained. In this work we determined the mean proton paths and the corresponding spatial uncertainty, taking into account the presence of the air gap

A novel analytical population tumor control probability model includes cell density and volume variations: application to canine brain tumor

Purpose: Tumor control probability (TCP) models based on Poisson statistics characterize the distribution of surviving clonogens. Thus enabling the calculation of TCP for individuals. To mathematically describe clinically observed survival data of patient cohorts it is necessary to extend the Poisson TCP model. This is typically done by either incorporating variations of model parameters or by using an empirical logistic model. The purpose of this work is the development of an analytical population TCP model by mechanistic extension of the Possion model. Methods and materials: The frequency distribution of gross tumor volumes was used to incorporate tumor volume variations into the TCP model. Additionally the tumor cell density variation was incorporated. Both versions of the population TCP model were fitted to clinical data and compared to existing literature. Results: It was shown that clinically observed brain tumor volumes of dogs undergoing radiotherapy are distributed according to an exponential distribution. The average gross tumor volume size was 3.37 cm3. Fitting the population TCP model including the volume variation using linear-quadratic and track-event model yieldedα=0.36Gy--1a, β=0.045Gy--2, a=0.9yr--1, TD=5.0d,and p=.36Gy--1, q=0.48Gy--1, a=0.80yr--1, TD=3.0d, respectively. Fitting the population TCP model including both the volume and cell density variation yielded α=0.43Gy--1, β=0.0537Gy--2, a=2.0yr--1, TD=3.0d, σ=2.5,and p=.43Gy--1, q=0.55Gy--1, a=2.0yr--1, TD=2.0d, σ=3.0,respectively. Conclusions: Two sets of radiobiological parameters were obtained which can be used for quantifying the TCP for radiation therapy of brain tumors in dogs. We established a mechanistic link between the poisson statistics based individual TCP model and the logistic TCP model. This link can be used to determine the radiobiological parameters of patient specific TCP models from published fits of logistic models to cohorts of patients

Retrospective evaluation of a robust hybrid planning technique established for irradiation of breast cancer patients with included mammary internal lymph nodes

Background: The irradiation of breast cancer patients with included internal mammary lymph nodes challenges radiation planning with regard to robustness and protection of OARs. In this publication, a feasible hybrid radiation technique is presented with a retrospective dosimetric and radiobiological analysis of patient data of our institute from 2016 to 2020 and robustness analysis. Methods: The proposed hybrid irradiation technique consists of two IMRT tangents and two partial VMAT fields. The retrospective dosimetric and radiobiological evaluation are made for 217 patient treatments (right- and left-sided). The robustness is evaluated regarding an artificial swelling from 0.4 to 1.5 cm for a random example patient and compared to a pure VMAT planning technique with use of a virtual bolus. The out of field stray dose is calculated for a selected patient plan and compared to alternative radiation techniques. Results: The coverage D_{95%} of the PTV$_{Eval}$ (with breast swelling of 1.5 cm) changes for the hybrid plan from 96.1 to 92.1% of prescribed dose and for the pure VMAT plan from 94.3 to 87%. The retrospective dosimetric evaluation of patient irradiations reveals a D$_{mean}$ for total lung 6.5 ± 0.9 Gy (NTCP[Semenenko 2008] 2.8 ± 0.5%), ipsilateral lung 10.9 ± 1.5 Gy, contralateral lung 2.2 ± 0.6 Gy, heart 2.1 ± 1.1 Gy (ERR[Schneider 2017] 0.02 ± 0.17%) and contralateral breast 1.7 ± 0.6 Gy. The scatter dose of the hybrid irradiation technique is higher than for pure VMAT and lower than for pure IMRT irradiation. Conclusions: The feasibility of the proposed planning technique is shown by treating many patients with this technique at our radiotherapy department. The hybrid radiation technique shows a good sparing of the OARs in the retrospective analysis and is robust with regards to a breast swelling of up to 1.5 cm. The slightly higher stray dose of the hybrid technique compared to a pure VMAT technique originates from higher number of MUs and lower conformity