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1.
Eur J Dent Educ ; 22(3): e303-e311, 2018 Aug.
Article in English | MEDLINE | ID: mdl-29148145

ABSTRACT

PURPOSE/OBJECTIVES: In view of the demographic shift, undergraduate dental students should be prepared for growing numbers of older people and their specific needs. The study examines changes in undergraduate dental teaching in Austria, Germany and Switzerland between 2004 and 2014. METHODS: Questionnaires were mailed in 2004, 2009 and 2014 to all deans and all department heads of Austrian (n = 4), German (n = 30) and Swiss (n = 4) dental schools. RESULTS: Response rates were 51% for deans and 47% for heads of department. Gerodontology was taught in 5 German universities, all 3 Swiss and 1 Austrian dental school. Aspects of gerodontology were included in traditional core subjects; however, in a large number of German (88%) and Austrian (50%) universities, dedicated lecture series and seminars are lacking. Changes over time indicate firmly established teaching in Switzerland, minor fluctuations in Austria and reduced dedicated teaching activities in Germany. CONCLUSIONS: Inclusion of gerodontology in the national syllabus is a decisive factor for the integration of the subject into undergraduate courses. The recommendations of the European College of Gerodontology (2009) regarding didactical and practical teaching should be implemented in the respective compulsory syllabus to prepare current undergraduate dental students for the challenges of tomorrow.


Subject(s)
Curriculum , Education, Dental/statistics & numerical data , Geriatric Dentistry/education , Austria , Germany , Schools, Dental , Surveys and Questionnaires , Switzerland
2.
Phys Med Biol ; 57(23): 8023-39, 2012 Dec 07.
Article in English | MEDLINE | ID: mdl-23160473

ABSTRACT

In order to provide a consistently high quality treatment, it is of great interest to assess the robustness of a treatment plan under the influence of geometric uncertainties. One possible method to implement this is to run treatment simulations for all scenarios that may arise from these uncertainties. These simulations may be evaluated in terms of the statistical distribution of the outcomes (as given by various dosimetric quality metrics) or statistical moments thereof, e.g. mean and/or variance. This paper introduces a method to compute the outcome distribution and all associated values of interest in a very efficient manner. This is accomplished by substituting the original patient model with a surrogate provided by a machine learning algorithm. This Gaussian process (GP) is trained to mimic the behavior of the patient model based on only very few samples. Once trained, the GP surrogate takes the place of the patient model in all subsequent calculations.The approach is demonstrated on two examples. The achieved computational speedup is more than one order of magnitude.


Subject(s)
Radiotherapy Planning, Computer-Assisted/methods , Uncertainty , Bayes Theorem , Humans , Male , Monte Carlo Method , Neoplasms/radiotherapy , Normal Distribution , Time Factors
3.
Phys Med Biol ; 57(12): 3693-709, 2012 Jun 21.
Article in English | MEDLINE | ID: mdl-22614733

ABSTRACT

We present a method of modeling dosimetric consequences of organ deformation and correlated motion of adjacent organ structures in radiotherapy. Based on a few organ geometry samples and the respective deformation fields as determined by deformable registration, principal component analysis (PCA) is used to create a low-dimensional parametric statistical organ deformation model (Söhn et al 2005 Phys. Med. Biol. 50 5893-908). PCA determines the most important geometric variability in terms of eigenmodes, which represent 3D vector fields of correlated organ deformations around the mean geometry. Weighted sums of a few dominating eigenmodes can be used to simulate synthetic geometries, which are statistically meaningful inter- and extrapolations of the input geometries, and predict their probability of occurrence. We present the use of PCA as a versatile treatment simulation tool, which allows comprehensive dosimetric assessment of the detrimental effects that deformable geometric uncertainties can have on a planned dose distribution. For this, a set of random synthetic geometries is generated by a PCA model for each simulated treatment course, and the dose of a given treatment plan is accumulated in the moving tissue elements via dose warping. This enables the calculation of average voxel doses, local dose variability, dose-volume histogram uncertainties, marginal as well as joint probability distributions of organ equivalent uniform doses and thus of TCP and NTCP, and other dosimetric and biologic endpoints. The method is applied to the example of deformable motion of prostate/bladder/rectum in prostate IMRT. Applications include dosimetric assessment of the adequacy of margin recipes, adaptation schemes, etc, as well as prospective 'virtual' evaluation of the possible benefits of new radiotherapy schemes.


Subject(s)
Models, Statistical , Movement , Radiotherapy Planning, Computer-Assisted/methods , Humans , Male , Principal Component Analysis , Prostatic Neoplasms/diagnostic imaging , Prostatic Neoplasms/physiopathology , Prostatic Neoplasms/radiotherapy , Radiometry , Tomography, X-Ray Computed
4.
Phys Med Biol ; 56(10): N123-9, 2011 May 21.
Article in English | MEDLINE | ID: mdl-21490384

ABSTRACT

Frequently, radiotherapy treatments are comprised of several dose distributions computed or optimized in different patient geometries. Therefore, the need arises to compute the comprehensive biological effect or physical figure of merit of the combined dose of a number of distinct geometry instances. For that purpose the dose is typically accumulated in a reference geometry through deformation fields obtained from deformable image registration. However, it is difficult to establish precise voxel-by-voxel relationships between different anatomical images in many cases. In this work, the mathematical properties of commonly used score functions are exploited to derive an upper boundary for the maximum effect for normal tissue and a lower boundary for the minimum effect for the target of accumulated doses on multiple geometry instances.


Subject(s)
Models, Biological , Radiation Dosage , Humans , Neoplasms/radiotherapy , Radiotherapy Dosage
5.
Z Gerontol Geriatr ; 44(3): 181-6, 2011 Jun.
Article in German | MEDLINE | ID: mdl-21505942

ABSTRACT

Oral health of long-term care (LTC) residents is often poor. From 30 random German LTC facilities, 242 random residents (Berlin n=75, Northrhine-Westfalia (NRW) n=94, Saxony n=73) (median age: 82 years, female: 78.5%) were interviewed as to their use of dental services, possession of a bonus booklet (BB), and completeness of records. Only 18.6% possessed a BB. Significant regional differences were observed (Berlin=5.3%, NRW=18.1%, Saxony=32.9%) (χ(2) test p<0.01). The number of teeth was higher (Mann-Whitney test p=0.01) and the time since last dental visit shorter (p<0.01) for all residents with a BB. Only 18.6% of people possessing a BB declared not having had a dental appointment within the previous 12 months (LTC residents without BB 51.3%). As a means towards improved quality management in nursing, better oral infection control of residents and increased oral health and general quality of life, the introduction of a regular annual preventive dental screening program including the use of a dental bonus system are suggested.


Subject(s)
Long-Term Care/statistics & numerical data , Motivation , Oral Health/statistics & numerical data , Oral Hygiene/statistics & numerical data , Patient Compliance/statistics & numerical data , Aged, 80 and over , Female , Germany/epidemiology , Humans , Male
6.
Med Phys ; 37(8): 4019-28, 2010 Aug.
Article in English | MEDLINE | ID: mdl-20879563

ABSTRACT

PURPOSE: Organ movement is still the biggest challenge in cancer treatment despite advances in online imaging. Due to the resulting geometric uncertainties, the delivered dose cannot be predicted precisely at treatment planning time. Consequently, all associated dose metrics (e.g., EUD and maxDose) are random variables with a patient-specific probability distribution. The method that the authors propose makes these distributions the basis of the optimization and evaluation process. METHODS: The authors start from a model of motion derived from patient-specific imaging. On a multitude of geometry instances sampled from this model, a dose metric is evaluated. The resulting pdf of this dose metric is termed outcome distribution. The approach optimizes the shape of the outcome distribution based on its mean and variance. This is in contrast to the conventional optimization of a nominal value (e.g., PTV EUD) computed on a single geometry instance. The mean and variance allow for an estimate of the expected treatment outcome along with the residual uncertainty. Besides being applicable to the target, the proposed method also seamlessly includes the organs at risk (OARs). RESULTS: The likelihood that a given value of a metric is reached in the treatment is predicted quantitatively. This information reveals potential hazards that may occur during the course of the treatment, thus helping the expert to find the right balance between the risk of insufficient normal tissue sparing and the risk of insufficient tumor control. By feeding this information to the optimizer, outcome distributions can be obtained where the probability of exceeding a given OAR maximum and that of falling short of a given target goal can be minimized simultaneously. CONCLUSIONS: The method is applicable to any source of residual motion uncertainty in treatment delivery. Any model that quantifies organ movement and deformation in terms of probability distributions can be used as basis for the algorithm. Thus, it can generate dose distributions that are robust against interfraction and intrafraction motion alike, effectively removing the need for indiscriminate safety margins.


Subject(s)
Data Interpretation, Statistical , Models, Biological , Models, Statistical , Movement , Radiotherapy Planning, Computer-Assisted/methods , Radiotherapy, Computer-Assisted/methods , Radiotherapy, Conformal/methods , Computer Simulation , Humans , Reproducibility of Results , Sensitivity and Specificity
7.
Phys Med Biol ; 53(22): 6337-43, 2008 Nov 21.
Article in English | MEDLINE | ID: mdl-18936521

ABSTRACT

The major challenge in intensity-modulated radiotherapy planning is to find the right balance between tumor control and normal tissue sparing. The most desirable solution is never physically feasible, and a compromise has to be found. One possible way to approach this problem is constrained optimization. In this context, it is worthwhile to quantitatively predict the impact of adjustments of the constraints on the optimum dose distribution. This has been dealt with in regard to cost functions in a previous paper. The aim of the present paper is to introduce spatial resolution to this formalism. Our method reveals the active constraints in a target subvolume that was previously selected by the practitioner for its insufficient dose. This is useful if a multitude of constraints can be the cause of a cold spot. The response of the optimal dose distribution to an adjustment of constraints (perturbation) is predicted. We conclude with a clinical example.


Subject(s)
Radiation Dosage , Radiotherapy, Intensity-Modulated , Algorithms , Humans , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted , Sensitivity and Specificity
8.
Article in German | MEDLINE | ID: mdl-3087095

ABSTRACT

A one-year-study was carried out in the waste-water treatment plant of Plön (population equivalents 60,000), which has a mechanical and a biological purification and an additional chemical flocculation. Samples were taken at five different places in the plant and examined for Salmonella by use of membrane-filtration and MPN-method. 2,611 Salmonella-strains, representing 23 species, were isolated and serologically typed from samples taken at ten days. S. typhi-murium was found most frequently (Table 1, Fig. 1). The largest spectrum of different types was located in the activated sludge-basin and at the outlet of the chemical flocculation (Table 2). No correlation could be established between the qualitative findings and the Salmonella-counts or other parameter like temperatures. All the ten species that have been officially reported to cause salmonellosis in man were also isolated from the sewage (Table 5). Findings of other Salmonella-serotypes are attributed to unreported human infections and animals or other sources.


Subject(s)
Salmonella paratyphi B/classification , Salmonella typhimurium/classification , Salmonella/classification , Water Microbiology , Germany, West , Humans , Salmonella/isolation & purification , Salmonella/pathogenicity , Salmonella Infections/microbiology , Salmonella paratyphi B/isolation & purification , Salmonella typhimurium/isolation & purification , Seasons , Serotyping
9.
Article in German | MEDLINE | ID: mdl-3087096

ABSTRACT

The paper offers the results of a one-year-survey of Salmonella-serotypes in a municipal sewage-purification plant with a capacity of roughly 70,000 m3 per day. Findings of a quantitative study had shown Salmonella-maxima in the activated-sludge-basin. This suggested specialized Salmonella-serotypes, resident in this part of the plant as a possible explanation which was to be verified by this study. On ten days samples were taken from the inlet, and the outlet of the primary-sedimentation-tank, the outlet of the activated-sludge-basin and the effluent of the final sedimentation-basin. A combination of membrane-filtration and MPN-Method with a fifefold enrichment in 2.5% tetrathionate was applied for salmonella isolation. Plating was done on malachit-green-chinablue-lactose-agar followed by serological typing. 1,587 strains representing 38 different serotypes (Table 1) were identified with S. typhi-murium (Fig. 1) accounting for 36% of the isolations followed by S. bovis-morbificans, S. hadar (Fig. 2) and S. panama. None of the serotypes found showed a preference of a special sampling point. The qualitative and quantitative distribution of Salmonella in the plant seems to depend on the Salmonella contents of the entering waste water mainly. The greatest variety of Salmonella-serotypes was located in the activated-sludge-basin (Table 2) where oxygen-enrichment seems to result in the best ecological conditions for Salmonella survival. 3.3% of 722 strains examined did not produce hydrogen-sulphide (Table 3) and some showed damaged flagella-antigens. As a possible explanation toxic influences in the sewage are discussed. The epidemiological links between findings of Salmonella in sewage and in man of the same area are established and results differing in some aspects explained by the high rate of unknown infections. The existence of an autochthonous Salmonella-population in the sewage plant could not be proved.


Subject(s)
Salmonella typhimurium/classification , Salmonella/classification , Sewage , Water Microbiology , Antigens, Bacterial/analysis , Germany, West , Humans , Hydrogen Sulfide/metabolism , Salmonella/growth & development , Salmonella/immunology , Salmonella/isolation & purification , Salmonella Infections/epidemiology , Salmonella Infections/microbiology , Salmonella enteritidis/classification , Salmonella enteritidis/growth & development , Salmonella enteritidis/isolation & purification , Salmonella paratyphi B/classification , Salmonella paratyphi B/growth & development , Salmonella paratyphi B/isolation & purification , Salmonella typhimurium/growth & development , Salmonella typhimurium/isolation & purification , Serotyping
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